Machine Learning Engineer at Toss Securities | Seoul

Join Our Team As a Machine Learning Engineer at Toss Securities, you will be part of the AI Tribe, collaborating with Data Engineers, Server Engineers, Frontend Engineers, Product Owners, and Product Designers. The AI Tribe aims to create data services that provide essential information to investors using data from various securities domains and cutting-edge Machine Learning technologies. Our focus is on developing personalized recommendation systems and utilizing LLM-based technologies. Your Responsibilities Develop personalized services based on diverse securities domain data and user behavior data. Experiment with reinforcement learning, deep learning, and machine learning methodologies to build recommendation models. Formulate and validate hypotheses regarding user information consumption, enhancing our services in the process. Define the criteria for recommendations and user profiles beyond simple item suggestions. Ideal Candidate Experience in validating hypotheses through personalization and recommendation systems in real-world applications. Strong foundational knowledge of recommendation system domains. Hands-on experience experimenting with and optimizing various deep learning and machine learning-based recommendation models. Familiarity with modeling based on actual user behavior data from apps. Resume Tips Detail your projects or services, including their objectives and outcomes. Focus on impactful projects or services. Explain the problems you solved and the technologies you used. If certain information is sensitive, please omit those details. Technologies Used at Toss Securities Predict user behaviors through User Modeling based on diverse user data. Build deep learning recommendation models by defining and utilizing User Features. Implement Multi-Armed Bandit (MAB) technology in our recommendation services. Generate and validate data as needed, fine-tuning and testing Large Language Models. Conduct experiments and build Retrieval/Chunking/Reranker/Generation models to establish RAG systems. Application Process Application Submission > Job Interview > Cultural Fit Interview > Reference Check > Compensation Negotiation > Final Offer and Onboarding Important Notes Any false information found in your resume or documents may lead to cancellation of your application. Individuals prohibited from hiring under Toss Securities regulations may have their applications canceled. Disabled individuals and those eligible for national veterans' benefits will be given preference in accordance with relevant laws. A Message to Future Colleagues “We are looking for colleagues who are ready to innovate financial services through Machine Learning technology!” Investors in the financial market require vast amounts of information to make informed decisions, but knowing what information to seek and where to find it can be challenging.

About the Team You Will Join The Machine Learning Engineer (LLM) at Toss Securities is part of the AI Tribe. You'll collaborate with various Data, Server, Frontend Engineers, Designers, and Product Owners to tackle product-level challenges. The goal of the AI Tribe is to simplify complex financial and securities information, delivering only the most relevant data to individuals through data and ML-based services. To achieve this, we experiment with a variety of ML techniques, including NLP/LLM training and operation, AI service development, and personalized recommendations, integrating these into real products. Your Responsibilities Upon Joining As a Machine Learning Engineer (LLM) at Toss Securities, you will take on two primary roles. If you excel in one area, you can still make significant contributions to the team. Model Training, Serving, and Operations You will train models suited for text-based challenges (e.g., classification, extraction, summarization, translation). Enhance model quality through fine-tuning, experimental design, and performance evaluation. Serve models in a live service environment and ensure their stable operation. Monitor performance degradation and changes in data distribution, implementing improvements as needed. Defining AI Service Problems, Data Construction, and AI Feature Design Reframe complex financial and securities domain issues into solvable ML/LLM problems. Define and construct datasets to facilitate model training. Generate advanced insights based on various financial data such as disclosures, news, and financial data. Collaborate with multiple teams to ensure AI features operate seamlessly within products. We Are Looking For Individuals with experience in creating and deploying LLM or NLP models. Those who have taken full responsibility for the entire cycle from data definition to model operation. Insights into utilizing LLMs effectively and reliably are a plus. Ability to logically explain why specific approaches are appropriate in problem-solving. Interest in the securities domain and simplifying complex information through technology. Preferred Qualifications Experience in developing and enhancing a single LLM/NLP model from start to finish. Experience analyzing performance degradation or data changes in service operations and implementing structural improvements. Experience improving AI features from the perspective of user experience or product metrics rather than solely model performance. Resume Recommendations Clearly state the problems you aimed to solve, the methods you chose, and the resulting changes (e.g., metrics or product modifications). Include improvements attempted during the operational phase, not just model development. Be specific about your roles within LLM, NLP, or services. Focus on the overall structure and your key contributions. Exclude sensitive information that cannot be disclosed publicly. The Journey to Joining Toss Securities Application Submission > Phone Interview > Job Interview > Cultural Fit Interview > Reference Check > Compensation Negotiation > Final Offer and Onboarding

About the Team You Will JoinThe Machine Learning Engineer (MLOps) will be part of the ML Platform Team at Toss Bank.This team is responsible for developing and operating the machine learning platform within Toss Bank.Your ResponsibilitiesCollaborate on the development of common technologies within the ML chapter.Build and manage internal machine learning platforms using MLFlow, Airflow, Jupyterhub, and Kubeflow.Operate ScyllaDB clusters and develop Feature Store services.Develop a model serving environment based on Triton Inference Server.Establish and maintain the internal LLM platform.We Are Looking ForExperience with developing, deploying, and operating services on Kubernetes.A strong interest in machine learning and awareness of the latest trends in the field.Experience handling high-traffic applications.Experience in developing and optimizing performance using GPU-based frameworks.Experience managing distributed databases such as Apache Cassandra and ScyllaDB.Experience in building and operating LLM serving or LLMOps platforms is a plus.Strong problem-solving skills and excellent communication abilities to find optimal solutions in various situations.Resume TipsClearly describe impactful projects you've worked on.Detail your experience in building and operating machine learning platforms, including troubleshooting during operations.If applicable, share quantifiable results from improvements made to live services (omit sensitive external data).Journey to Joining Toss BankApplication Submission > Live Coding Test > Job Interview > Cultural Fit Interview > Reference Check > Compensation Discussion > Final Acceptance and OnboardingPlease NoteAny false information found in your resume or disciplinary actions in your work history may lead to cancellation of employment.Applicants who fall under the disqualification reasons per Toss Bank's employment regulations may have their applications canceled.Priority will be given to disabled individuals and national veterans in accordance with relevant laws.

# Join Our Team The Machine Learning Engineer (Service) will be part of the ML Tribe within the Data Division at Toss Bank. Our team aims to tackle challenges in the financial sector that have been unaddressed, utilizing AI technologies (LLM, ML) to optimize operations and maximize profitability. Your Responsibilities Develop and operate agents aimed at optimizing financial operations. Design and develop systems for serving stable and scalable financial ML models. Ideal Candidate Profile Experience in developing and operating ML services with high SLAs in high-traffic environments is essential. Proficient in designing service architectures that balance stability and scalability, while writing maintainable, high-quality code. Experience or interest in optimizing work through agents is preferred. Familiarity with technologies such as FastAPI, LLM, Agent, Kafka, Spark, Flink, and Airflow is a plus. A track record of leveraging AI technologies to solve complex problems or develop impactful services/products is desirable. Resume Writing Tips Showcase practical development experience with concrete examples. Detail the technical challenges you have addressed and how you implemented solutions. If applicable, describe experiences comparing the cost-effectiveness of choices made between architectural complexity and development resources. Highlight projects that have generated business impact. If you have experience applying developed products in production environments and refining them based on performance metrics, please include that. Your Journey to Joining Toss Bank Application Submission > Live Coding Test > Technical Interview > Cultural Fit Interview > Reference Check > Compensation Discussion > Final Acceptance and Onboarding Please Note Employment may be rescinded if any false information is found in the resume or if there are disciplinary issues in your work history. Applicants who fall under the disqualification criteria as per Toss Bank's employment regulations may have their applications canceled. Individuals with disabilities and veterans are given preferential treatment in accordance with relevant laws.

Join Our Security Team! The security team at Toss Securities is composed of dedicated professionals, including a CISO, Security Engineers, Security Researchers, Information Security Managers, and Privacy Managers. We are committed to creating secure services, receiving robust support from the entire organization, and collaborating effectively across all departments. Our team members, with diverse experience ranging from 1 to 20 years, primarily come from backgrounds in information security firms and corporate security roles. We actively share knowledge and collaborate to achieve common goals. To ensure the safe operation of our securities services, we conduct vulnerability assessments across various fields such as applications, cloud, infrastructure, and network. We are also developing automated testing systems using DAST, SAST, and IAST tools to enhance our testing framework. Your Responsibilities: Collaborate with relevant departments from the service planning stage to perform security reviews and provide guidelines for safe service implementation. Conduct vulnerability assessments on Toss Securities' internal and external services (WTS, MTS, operational systems, etc.), analyze results, and suggest improvements. Perform infrastructure vulnerability assessments as required by electronic financial regulations and domestic/international security certifications (Public/Private Cloud, Server, DBMS, Network, etc.). Execute scenario-based internal/external penetration tests and conduct preliminary checks to prevent internal information leaks. Who We're Looking For: Individuals with over 7 years of experience in vulnerability assessments. Experience in operating or conducting assessments with infrastructure vulnerability assessment tools. Experience in developing tools or automation programs for vulnerability assessments. Ability to perform REST API vulnerability assessments based on an understanding of MSA environments. Experience in security audits identifying vulnerabilities such as IDOR in Java or Kotlin source code. Experience in assessing application vulnerabilities in Android or iOS environments. Understanding of electronic financial services and securities systems is a plus. Experience or understanding of Attack Surface Management is a bonus. Application Tips: Include any services or programs you've developed or participated in, specifying the language, role, deployment status, and operational environment. Detail specific vulnerabilities identified through SAST, DAST, Image Scanning, Secret Scanning, and your corrective actions (company/service names can be anonymized). Explain how you assessed and responded to actual security incidents or potential risks, such as secret exposure or high-risk image vulnerabilities. Share challenges and solutions encountered during security assessment automation or policy application processes. Hiring Process at Toss Securities: Application submission > Job interview > Cultural fit interview > Reference check > Salary negotiation > Final acceptance and onboarding. Additional Information: Providing false information in your resume or discovering disciplinary actions in your employment history may lead to termination of the recruitment process.

Join Our Team! The Network Engineering team is tasked with establishing Toss Securities' network and security systems, along with managing data center operations. We collaborate with exceptional team members from diverse sectors including finance, commerce, portals, and gaming. Our goal is to support product focus by ensuring infrastructure capable of handling large-scale traffic and driving automation for quicker product releases. Your Responsibilities: Install and maintain Toss Securities' network and security devices, conducting regular status checks and resolving operational issues. Register and manage asset information for network and security devices (serial numbers, status, locations, etc.). Document work logs and change history for installation, migration, and decommissioning tasks. Oversee and enhance Toss Securities' network monitoring solutions. Provide rapid onsite response and first-level troubleshooting during incidents. Plan and support schedules for regular inspections of network and security devices. Be available for night or weekend maintenance when necessary. Manage cable connections for servers and storage, supervising cable installation by contractors. Who We Are Looking For: At least 5 years of experience in network technical support and field engineering. Understanding of network cabling standards and wiring practices is essential. Ability to respond effectively to incidents and perform basic network troubleshooting. Experience in collaborating with maintenance vendors and managing inspection documentation. Operational experience with major network equipment like Cisco and Arista is required; experience with Citrix NetScaler is a plus. Familiarity with security devices such as firewalls and VPNs, alongside a strong understanding of network security is preferred. Application Recommendations: In your resume, highlight a memorable case of technical problem-solving (optimization, bug fixing, etc.). Detail projects you've contributed to, including duration, roles, technology stack used, and improvements made. Your Journey with Toss Securities: Application submission > Job interview > Cultural fit interview > Final acceptance and onboarding. Please Note: This position is a contract role with a duration of one year. Any discrepancies in the resume or disciplinary records may result in cancellation of employment. Applicants subject to hiring restrictions or disqualifications as per Toss Securities' policies may have their applications canceled. Applicants with disabilities or veterans will receive preferential treatment in accordance with relevant laws. A Note for Future Colleagues: “At Toss Securities, you can experience both the constraints of a financial infrastructure and the trendy mobile services of an IT company!” The financial infrastructure in South Korea can be quite restrictive, limiting the breadth of experiences. However, at Toss Securities, you have the responsibility and authority to implement solutions that benefit the business, allowing for valuable experiences without being bound by irrelevant solutions dictated from above.

Join Our Dynamic Team As a DevOps Engineer at Toss Securities, you will be an integral part of our DevOps & SRE team. You will innovate the deployment process by applying various technologies and tools, enabling developers to deploy services with ease. In the event of system failures, you will derive intuitive metrics to identify root causes, ensuring all developers can respond swiftly to incidents. Utilizing Kubernetes and the Cloud Native ecosystem, you will enhance large-scale systems to their fullest potential. Your Responsibilities Will Include Previously focused on improving operational experience, we are now dedicated to eliminating fatigue and inefficiencies in the development experience. You will manage monitoring, incident response, and troubleshooting tasks, continuously analyzing developer experiences and overseeing the development and operational enhancements. We Are Looking For Candidates Who Have relevant experience in container orchestration, as it is a primary responsibility of this position. Possess experience in network troubleshooting, as this is a challenging aspect of the role. Can automate engineering experiences or create tools for improvements within their current organization. Thrive in a collaborative environment where teamwork is key, and can identify and eliminate inefficient processes based on their engineering experiences. Resume Recommendations Outline your experience managing infrastructure based on Kubernetes + Istio. Detail your experience building and operating metric systems in large-scale distributed environments. Include your experience in operating services based on container orchestration and CI/CD servers. Mention your experience with AWS cloud services. Technologies Used at Toss Securities Kotlin, Java, Gradle Netty, Spring MVC, Spring Webflux, Spring Boot, Spring Cloud Gateway, Spring Cloud Config JPA/Hibernate, MySQL, MongoDB, Hadoop, Redis, Memcached, Zookeeper Kubernetes + Istio, HAProxy, Nginx GoCD, ArgoCD, Consul, Vault, Git, Docker, Spinnaker, Jenkins, Ceph, Harbor Kafka, ELK, Prometheus + Thanos, InfluxData, Grafana

Join Our Dynamic TeamThe Data Engineer (AI) position is part of the AI Data Platform Team at Toss Securities.The AI Data Platform Team comprises Data Engineers, Machine Learning Engineers, Server Engineers, and Product Operation Managers, fostering collaboration across various roles.Our mission is to develop a unique data moat for Toss Securities through the integration of diverse securities domain data and AI technologies, providing essential insights for investors.We utilize external LLMs and conduct training and evaluation of our internally developed models while leveraging various data platform technologies.Your ResponsibilitiesProactively identify and lead projects to solve business challenges at Toss Securities, overseeing the entire process from data architecture design to development and operation.Build and manage a securities data platform that integrates, processes, and serves global market data.Establish and maintain a knowledge graph platform for real-time domain data.Create and operate data pipelines that underpin AI service products.Develop and manage a feature store for personalized recommendation services in real-time.Ensure data integrity by designing, developing, and operating data quality verification and monitoring systems.We Seek Candidates WhoHave over 5 years of experience in data engineering.Can comprehend requirements and analyze technical trade-offs to determine the optimal data architecture in a given environment.Possess a solid understanding and experience in large-scale distributed processing and data platforms.Have experience sharing knowledge with peers and junior engineers, contributing to the technical growth of the entire team.Are interested in leveraging AI beyond mere tools, understanding its principles to innovate engineering productivity.Can coordinate with colleagues across various functions and provide constructive feedback.Are eager to take on new challenges and proactively learn and grow.Preferred ExperiencesExperience with Kafka-based stream processing and large-scale distributed data processing (Hadoop/ClickHouse/ElasticSearch).Experience building and operating data pipelines using Airflow, Docker, and Kubernetes.Experience in monitoring and managing data integrity and quality.Stay up-to-date with the latest trends in AI/data technologies and have an interest in automation and productivity enhancement.

About the Team You Will Join The Data Engineer (Search) at Toss Securities is part of the AI Tribe within the AI Intelligence Silo. This Silo is a collaborative team consisting of Data Engineers, Machine Learning Engineers, Server Engineers, Frontend Engineers, Product Owners, and Product Designers, all working towards creating AI-driven information services leveraging securities domain data. Our focus is not just on presenting information but on rapidly experimenting with how to process and present data in a way that assists investors effectively. Search acts as the primary entry point connecting various securities data and AI services, with the Data Engineer (Search) being responsible for search/indexing functionalities that can be utilized across AI-based data services. The role centers around designing and operating the data and indexing aspects that constitute our search services, concentrating on stably designing and managing the data flow and infrastructure for search indexing rather than just enhancing algorithms or ranking models as seen in larger portals or e-commerce. Key Responsibilities Design and manage the indexing pipeline for Toss Securities search services, including stocks, autocomplete, news, and community features. Architect and reliably operate real-time/big data pipelines for search indexing. Gain insights into Elasticsearch-based search indexes and enhance the indexing structure and performance from a data perspective. Collaborate on data integrity management and re-indexing strategies to ensure stable data delivery for search. Gradually expand your responsibilities into areas beyond search, such as Graph search and ingestion of new data sources. Who We Are Looking For A candidate with over 3 years of experience in Data Engineering. Strong programming skills are preferred. Experience in designing or operating real-time or batch-based data pipelines is a plus. Experience in collecting and processing diverse data sources for service utilization is beneficial. Familiarity with big data processing platforms such as Spark, Hadoop, Impala is an advantage. A passion and curiosity for learning new domains and technologies are highly valued. A preference for collaborative environments where feedback and growth are encouraged is ideal. Additional Preferred Experience Experience using or managing search service infrastructures like Elasticsearch, Lucene, or Solr is advantageous. A genuine interest or experience in search domains such as search engines, recommendations, or ranking systems is a plus. Resume Tips Please detail your experience in designing/developing/operating data pipelines, ETL, streaming, etc. Highlight your role in projects and what you learned and improved through those experiences. If you have experience with search or Elasticsearch, even on a smaller scale, please describe the problems you solved. Your Journey to Joining Toss Securities Application submission > Job interview > Cultural fit interview > Reference check > Compensation discussion > Final acceptance and onboarding

Join Our Innovative TeamThe Machine Learning Engineer (Infra) will be part of the ML Platform Team within the Product Division at Toss Securities.The primary goal of the ML Platform Team is to create an optimal machine learning platform that enables the efficient and stable development and operation of various AI/ML services at Toss Securities.The ML Engineer (Infra) will focus on maximizing the efficiency of large-scale AI infrastructure, finely controlling resource usage, and enhancing infrastructure performance to its peak. Your Responsibilities Design and operate high-performance AI computing environments reliably.Design and operate top-of-the-line GPU clusters (H100, B300 series) connected via InfiniBand and high-performance storage (400Gbps) within a Kubernetes environment.Beyond merely building infrastructure, optimize networks and storage to extract the full potential of hardware performance. Develop a comprehensive control system for the entire AI infrastructure.Create an observability system to integrate and monitor AI resources distributed across internal infrastructure and external cloud.Implement management features to prevent resource monopolization by specific services and allocate resources precisely based on importance. Create automation tools for the most efficient resource usage.Analyze actual usage patterns to develop tools that recommend 'just-right resources' to avoid waste.Implement features that automatically scale up or down based on real-time model performance or error rates, and reallocate GPUs where necessary. Establish an environment for identifying and resolving model performance bottlenecks.Build profiling environments to accurately pinpoint slowdowns during model training or serving.Support the analysis and improvement of performance degradation causes between hardware and software. Who We Are Looking ForYou have experience building and operating Kubernetes-based ML infrastructures that handle large-scale traffic.You take responsibility for reliably operating live services beyond simple development.You have experience persistently analyzing and debugging to resolve root causes when issues arise.You possess a solid understanding of system resources (GPU/CPU/Memory/Network/Storage) and have experience building monitoring systems for them.You value the process of solving various problems that arise during service operations and strengthening the system. Preferred QualificationsExperience in unified monitoring of resource usage in large-scale clusters.Experience building systems to systematically control resources through Quota and Rate Limits.Experience with open-source platforms like Kubeflow or Kubernetes, including in-depth modifications as needed.Experience analyzing and optimizing bottlenecks at the kernel level using tools like Nsight Systems/Compute or PyTorch Profiler.Experience designing tasks to reduce costs or enhance performance tailored to workload characteristics (Rightsizing, Cost Optimization).Experience leveraging GPU virtualization technologies like MIG and MPS to maximize resource utilization.

About the Team You'll Join The ML Engineer (Platform) at Toss Securities is part of the ML Platform Team within the Product Division. The mission of the ML Platform Team is to create an optimal machine learning platform that enables efficient and stable development and operation of various AI/ML services at Toss Securities. Your Responsibilities Upon Joining Develop and enhance the Gateway system, the gateway for ML services. Develop and operate a Gateway system based on FastAPI that handles enterprise-level LLM API requests. Design and implement authentication, routing, traffic control, fault isolation (Circuit Breaker, Fallback), large-scale TPS processing, and load balancing strategies from both application and infrastructure perspectives in the FastAPI-based Gateway application. Manage and serve ML services. Directly operate a machine learning model serving system in a Kubernetes environment. Design and improve the LLM serving architecture to operate stably under large traffic conditions. Monitor latency, error rates, resource usage, and analyze and resolve operational issues for the models in service. Identify root causes of failures and implement structural improvements, including operational policies and architecture. Develop and manage a common ML platform for the company. Develop and manage a common platform for efficiently operating the training and serving of internal ML/LLM models based on Kubeflow. Continuously monitor and optimize the performance and resources of workloads executed on the platform. Build infrastructure for LLM-based services. Operate LLM services using various serving frameworks such as vLLM, SGLang, and Triton. Manage the environment to ensure stable operation of training and serving workloads on high-performance GPU clusters like H100/B300. Build and operate a large-scale data training environment for finance domain-specific LLMs. We Are Looking for Candidates Who: Are proficient in one or more programming languages such as Python, Go, Java, or Kotlin, and have experience designing and developing API servers in production environments. Have experience developing or operating API Gateways (Nginx, Kong, etc.) or LLM Routers (LiteLLM, Envoy AI Gateway, etc.), with a background in handling high-volume traffic and incident response. Have experience operating serving logs and event pipelines integrated with Kafka, Elasticsearch, and Kibana. Have experience defining monitoring metrics for model serving and configuring and operating dashboards using Prometheus and Grafana. Have experience operating ML/LLM model serving using KServe, BentoML, vLLM, SGLang, etc. Have experience directly managing MLOps components (Kubeflow, KServe, Airflow, Argo CD, MLflow, etc.) in Kubernetes environments and debugging and resolving issues. Can design and apply long-term improvement plans through root cause analysis beyond short-term responses to issues that arise during service operations. Additional Preferred Experience: Experience in related fields or technologies will be a plus.

Join Our Team!The Data Engineer (DataOps) at Toss Securities is part of the Data Infra Team within the Data Division.The Data Infra Team manages a big data infrastructure based on the Hadoop ecosystem and operates a log/search platform (Elasticsearch). We provide technical support for Kubernetes, which is widely used for data acquisition and various data operations. Additionally, we are developing a data analysis platform aimed at enhancing the company's data literacy. Curious About the Data Division?The Toss Securities Data Division strives to become the world's leading securities firm in data management by contributing to data technology, services, and data-driven decision making.A diverse range of data professionals collaborate closely and enjoy their work.We regularly host Tech Weekly sessions to share expertise. If you are interested and willing, you can learn from various roles and their methodologies. Your Responsibilities Include:Operating and Improving a Stable Log PlatformThe log platform (Elasticsearch) at Toss Securities stores logs generated from various services, making it a key tool for securities service operations.You will innovate to ensure real-time data acquisition and fast search capabilities, handling millions of records per second.Managing the Toss Securities Search PlatformWe utilize an Elasticsearch-based search platform to provide a variety of search services for stocks, news, and content.You will collaborate with search engineers to create an environment for accurate and rapid searches without delays.Operating and Supporting Data KubernetesVarious engineers (Data Engineers, ML Engineers, DW Engineers, Search Engineers) in the Data Division use dedicated data Kubernetes for data acquisition, serving, and internal operations.The Data Engineer (DataOps) will address issues arising from the Data Kubernetes infrastructure and continuously develop the system from a long-term perspective.You will also analyze the experiences of data engineers, focusing on process development, operation, and enhancement tasks. We Are Looking For Candidates Who:Have over 5 years of experience as a Data Engineer.Have experience using or operating search engines like Elasticsearch or Solr.Have worked with or managed distributed databases.Have experience operating Kubernetes + Istio-based infrastructure.Understand or have experience with the Hadoop ecosystem.Have built and managed metric systems in large-scale distributed environments.Have experience operating container orchestration services and CI/CD servers.Can automate engineering experiences within their current organization and improve processes or tools.Possess the ability to eliminate poor funnels in engineering experiences, as our organization focuses on collaborative achievement rather than direct supervision. Technologies We Use at Toss Securities:Python, Kotlin, Java, Spring Boot, Spring Cloud ConfigElasticsearch stack, Opensearch stack, Vector

Join Our Team! At Toss Securities, our Server Chapter is filled with enthusiastic colleagues who are eager to collaborate and create meaningful advancements. We thrive on constructive discussions and innovative problem-solving, where every idea is valued, and constructive criticism is encouraged. We enjoy engaging in technical discussions and hold various study sessions. Whether you're new to the field or an experienced professional, you'll find opportunities to expand your knowledge and apply what you've learned in practical ways. Our active code review process ensures that you gain hands-on technical expertise. As a Server Developer at Toss Securities, you'll work across various teams, including Product Owners, Designers, Frontend Developers, and Data Analysts, in a dynamic environment similar to a startup. You'll also engage with specialized teams managing core financial data and ensuring the stability of our services. We are dedicated to developing back-office products that alleviate the inconvenience of visiting physical locations, creating a seamless experience for our users. Worried about communication with fellow developers across different teams? Don't be! Our community supports strong collaboration through code reviews, Engineering Days, and weekly Server Chapter meetings. Your Responsibilities We primarily utilize Java/Kotlin and the Spring Framework for server development. You will engage in selecting and standardizing efficient development practices and libraries. You will also focus on improving our architecture for easy deployment and maintenance, ensuring stability and performance. Working with technologies like Redis, Kafka, Kubernetes, and ELK, you'll tackle challenges related to high traffic and concurrent processing. You will be responsible for creating various aspects of the Toss Securities service, from real-time data processing to managing user account information and stock transactions. You will have ownership of your product areas and will make key technical decisions. Who We Are Looking For We seek individuals who are persistent problem solvers. You should be comfortable tackling complex challenges and delivering valuable solutions for our customers. A broad mindset is essential, as we sometimes need to take bold steps to simplify issues. We value individuals who are open to collaboration and are willing to take initiative, even when responsibilities may not be clearly defined.

# Join Our Team- As a Machine Learning Engineer (MLE) for Home Recommendations, you will play a crucial role in optimizing the recommendation strategies for various content, services, promotions, and messages within the Toss app using machine learning.- Your work will involve precisely modeling the effectiveness of different content at various user touchpoints such as the top of the Toss home screen, banners after money transfers, and push notifications, while continuously improving actual recommendation outcomes.- To enhance the quality of recommendations across diverse areas, you will focus on quantitative performance forecasting and the design of sophisticated exposure strategies.# Responsibilities- Design and enhance recommendation models for content, services, and promotions displayed across the Toss app.- Develop models to predict appropriate recommendations and responses (e.g., CTR) based on user behavior, timing, and context.- Engage in iterative improvement of recommendation systems through feature discovery, experimental design, and performance evaluation.- Optimize exposure strategies for various recommendation areas and push messages based on user responses, quantitatively measuring actual performance.# Who We Are Looking For- Individuals with practical experience dealing with recommendation systems, ranking, and personalization modeling are essential.- A background in designing and experimenting with CTR prediction, user response prediction, and ranking modeling is crucial.- Experience in feature engineering and model performance enhancement using user behavior data is required.- Proficiency in major ML frameworks such as PyTorch, TensorFlow, and LightGBM is necessary.- Candidates who have improved actual service performance through iterative experimentation and quantitative analysis will be preferred.- The ability to clearly define problems and explain them technically while collaborating with diverse teams is highly valued.# Resume Tips- Please detail any projects you have worked on that have had significant organizational impact.- Specify the problems you defined, the approaches you chose, the experimental methods, and how you improved performance in modeling-centric projects.- Highlight any processes where you quantitatively solved problems through iterative experiments and performance analysis.# Application Process- Application Submission > 1st Technical Interview (Coding) > 2nd Technical Interview > Cultural Fit Interview > Reference Check > Compensation Negotiation > Final Acceptance- The first technical interview will include a simple coding test, resume check, and a basic ML knowledge assessment.- The second technical interview will involve in-depth technical questions and discussions on ML system design.# A Message for Future Colleagues- "This role is not just about modeling; it's about making an impact on the business."- The most satisfying aspect of working at Toss is that we do more than just modeling.- Previously, the work was limited to inputting data into existing models and evaluating performance, but now we focus on how to incorporate unaggregated data into our models.- It is rewarding to contribute to running a super app based on a deep understanding of users, moving beyond just analyzing and modeling financial-related data!

Join us as a Technical Product Owner specializing in AI!The Technical Product Owner at Toss is a vital part of our team, driving the success of technology-driven products across various services.This role focuses on rapidly experimenting with AI/ML-based features and connecting them with real user experiences.Your responsibilities will include:Leading the end-to-end planning and improvement cycles of ML-based products.Defining and executing how technology should function in areas like recommendations, rankings, search, and personalization.Collaborating closely with Data Scientists and ML Engineers to bridge technology and product.Defining business impact, designing metrics, and enhancing products through A/B testing and iterative processes.Designing AI-driven user experiences, business structures, and technical architectures with a long-term perspective.We are looking for someone who:Has practical experience designing and operating machine learning-based products or systems.Possesses strong interest or experience in various ML applications such as recommendations, rankings, predictions, search, personalization, demand forecasting, and ad optimization.Has experience leading complex and uncertain tasks to completion.Can create incremental outcomes while considering both business impact and technical feasibility.Resume Tips:Clearly outline the flow from problem definition to solution generation, stakeholder collaboration, and final results for each product, service, or project.Instead of merely listing duties, highlight your achievements and insights gained throughout the process.Journey to join Toss:Application submission > Job interview > Cultural fit interview > Reference check > Compensation negotiation > Final acceptance and onboarding.“We are a team genuinely committed to delivering the best results to our users right now.”Recommendations, searches, and rankings are not merely technical problems.We need to design and solve complex issues involving customer context, our business strategy, and real-time data flows.There are no absolute answers, and we must always validate through A/B testing. Hence, this team speaks through experiments rather than opinions and metrics rather than assertions.If you love technology and want to lead the transformation of that technology into real user experiences and metrics, you will find exciting opportunities here.

About the Team You'll Join The Compliance Manager at Toss Securities is an integral part of the Compliance Division, specifically within the Compliance Team. This team is responsible for establishing and operating internal control systems essential for the development of Toss Securities' innovative products and services, as well as conducting pre-reviews to prevent legal risks. Team members collaborate and share their expertise based on their individual specializations to achieve common objectives. Your Responsibilities Upon Joining [Business Compliance Advisory] Analyze relevant regulations at the time of launching new services and design practical alternatives to mitigate risks. Provide compliance reviews in close communication with operational departments (Tribe/Silo). [Internal Control Inspections] Identify tasks requiring internal control inspections and establish inspection policies and measures. Enhance internal control checklists by department and improve the inspection process. When issues are detected during inspections and monitoring, derive corrective measures and communicate them to operational departments for follow-up. We Want to Work With Someone Who Has a minimum of 3 years of experience in compliance monitoring or legal affairs in a securities firm. Possesses practical knowledge of core business logic in the securities industry (e.g., brokerage, advisory/management services). Has experience in establishing diverse inspection and monitoring policies related to internal controls based on a strong understanding of retail services and mobile business. Exhibits excellent communication skills for collaboration with operational departments. It Would Be Great If You Also Have Experience collaborating with product teams. A strong understanding of control logic for various financial products. Knowledge in other internal control areas such as AML, consumer protection, and personal credit information. Experience dealing with regulatory bodies, such as responding to inspections by the Korea Exchange. Resume Submission Tips Clearly outline your actual monitoring, inspection, and improvement measures performed by task. If you have experience in establishing various inspection and monitoring policies related to internal controls based on a strong understanding of retail services and mobile business, please detail that. Describe experiences where you presented alternatives instead of a simple 'No' when faced with unreasonable demands from operational departments. If you have examples of process improvements that not only strengthened internal controls but also created value, please provide details of the improvements and their impacts. Your Journey to Joining Toss Securities Application Submission > Job Interview > Cultural Fit Interview > Reference Check > Compensation Discussion > Final Offer and Onboarding Please Note Employment may be rescinded if false information is found in your resume or if disciplinary actions during your employment history are confirmed. Employment may also be rescinded for candidates who fall under prohibited hiring categories or have disqualifying factors as per Toss Securities' internal regulations.

Join Our Audit Team Our audit team plays a crucial role in identifying and enhancing enterprise risks. We assess internal control systems and collaborate with various departments to drive tangible improvements. Guided by our motto, “Audit proactively like a vaccine, and protect as a shield until the end,” we approach our auditing tasks with a commitment to identify risks early and take responsibility for outcomes. As the regulatory environment in the securities industry becomes increasingly complex with the launch of new products, proactive risk assessments and collaboration with colleagues are vital to ensuring comprehensive control integrity across the business. Your Responsibilities Conduct in-depth audits related to regulatory compliance frameworks and internal control design following new license acquisitions (consulting/trading). Lead reviews of regulatory compliance and control appropriateness throughout the entire process of new product and service launches (including planning, development, and operations). Analyze the Financial Supervisory Service's sanctions database and financial consumer protection issues to incorporate them into audit items, deriving proactive prevention measures. Provide expertise and review monitoring rules developed in collaboration with RegTech specialists from the perspective of securities regulations and product controls. Manage the quality of regulatory and product-related documentation during inspections by supervisory agencies, supporting effective responses. We Are Looking For A candidate with over 10 years of experience in compliance, auditing, or risk management within financial investment companies or related organizations. A deep understanding of core securities regulations, including the Capital Markets Act, Financial Consumer Protection Act, and investor protection regulations, along with strong interpretive skills. Experience in reviewing regulatory compliance or control design/operations for new financial products or services throughout their entire launch process. Ability to diplomatically mediate conflicts with audit target departments and provide logical feedback centered on improvement rather than criticism. Experience participating in the development of RegTech or data-driven regulatory monitoring systems, providing regulatory/business perspective expertise is a plus. Possession of professional auditing certifications (CISA, CIA, etc.) or legal/accounting qualifications related to regulation is an advantage. Resume Tips Detail specific cases where you identified proactive regulatory risks during new license acquisition or product launch processes and led them to substantial control improvements, focusing on applicable laws and control items. If you have worked with IT specialists such as RegTech/DA auditors to incorporate regulatory control elements into IT systems or designed data monitoring rules, please emphasize this experience. Highlight your role and key achievements in preparing materials related to regulatory interpretation and product processes if you have experience responding to supervisory agency inspections. Emphasize fact-based examples of logical mediation and consensus-building among stakeholders (business departments) during internal control improvement processes. Application Process at Toss Securities Application submission > Job interview > Cultural fit interview > Reference check > Compensation negotiation > Final acceptance and onboarding A phone interview may be conducted if necessary. Please Note Any false information found in the resume or disciplinary records during employment history may lead to cancellation of the recruitment process. Individuals who are prohibited from hiring according to Toss Securities' internal regulations or have disqualifying reasons may have their applications canceled. Individuals with disabilities and those eligible for national veterans' benefits are given preference in accordance with relevant laws. A Message for Future Colleagues The audit team at Toss Securities aims not just to point out issues but to drive substantial improvements and proactive risk responses, fostering a culture of continuous enhancement.

Join Our Team!As a Node.js Developer at Toss Securities, you will be part of the Automation Platform Team.The Automation Platform Team is dedicated to creating and managing customer-facing services that provide a unique experience for users of Toss Securities, along with internal services that support these offerings.Your role will involve designing and implementing a range of automation platforms that help employees and customers shift their focus from repetitive tasks to more valuable work. What You Will Do:Develop Node.js-based applications that operate in diverse environments, including server and client-side applications.Write libraries and test code to create stable and observable services. We Are Looking For:A candidate with a deep understanding of Node.js, TypeScript, and Nest.js, or someone with ample practical experience in other server-side environments (like Spring) who is ready to transition to the Node.js ecosystem.Experience in designing and operating distributed applications, with the ability to define and resolve issues related to concurrency, atomicity, and parallel processing.Familiarity with log collection and monitoring for stable service operations.Ability to write flexible, readable, and maintainable code.Skills in identifying repetitive or inefficient processes and proposing better alternatives. Resume Tips:Describe challenges encountered during projects and how you solved them.Summarize your thoughts on good coding or design philosophy. Technologies Used at Toss Securities:Typescript, NestJS, pnpm, VitestELK Stack, ZooKeeper, Redis, Kafka

Join Our Team!The Machine Learning Backend Engineer will be part of the ML Service Team, developing backend servers and common service platforms for various AI products within Toss Bank.The ML Service Team consists of Data Scientists, responsible for model development and application, and ML Engineers, who focus on server development, collaboratively creating innovative AI solutions.We work closely with product organizations responsible for banking services, leveraging AI technology to develop products. Collaboration with POs, designers, and developers ensures we manage the complete development cycle of AI products.Your Responsibilities:Design and develop robust server architecture to ensure a stable delivery of diverse AI products handled by the ML Service Team.Create individual services capable of handling large-scale traffic based on a solid server architecture.Develop servers that can efficiently serve heavy computational AI models with reliable response times and throughput.Operate services that allow distributed tracing in a microservices architecture while minimizing disruptions.We Are Looking For:Experience in server development and operation using one or more programming languages such as Python, Kotlin, or Go.Ability to design resilient service architectures and implement stable code structures.Experience deploying and monitoring servers in Kubernetes environments for stable operations is a plus.Experience and skills in developing and operating production services that handle high traffic or have stringent SLAs are desirable.A background in solving large and complex problems through software technology or creating business impact through services or products is advantageous.No prior ML experience is required, but a strong interest in AI/ML and a desire to gain experience in this area is welcomed.Resume Recommendations:Provide concrete examples of practical server development experience in your resume.Include details about technical considerations and your actual implementations while solving problems.If you have experience comparing costs and benefits among choices when balancing architectural complexity and development resources, please include that.Detail any projects that have made a business impact.Discuss experiences where you applied developed products in production and refined them based on performance metrics.Your Journey to Joining Toss Bank:Application submission > Live coding test > Job interview...

# About the Team- As an MLE (Commerce Recommendation) in the Toss Commerce domain, you will play a pivotal role in optimizing product visibility.- Our focus is on designing and enhancing recommendation models based on diverse data sources to present users with more relevant and appealing products.- This team leads the full spectrum of machine learning development, from problem definition to training, performance analysis, and enhancement.- We are building a product recommendation platform that provides meaningful shopping experiences for users by leveraging various ML techniques.- **Interested in learning more about Toss's Data Organization?** [→ *Toss Data Division Wiki*](https://recruit-data-division.oopy.io/)# Responsibilities- Develop models to predict product click-through rates (CTR), conversion rates (CVR), and other key metrics based on user behavior, product information, and contextual data.- Design and refine recommendation algorithms to optimize product exposure using predictive outcomes.- Conduct iterative experiments including model performance analysis, feature engineering, and hyperparameter tuning to enhance recommendation quality.- Quantitatively validate the impact of model improvements through various experiments and offline/online performance metrics.- Collaborate with domain experts and data analysts when necessary to accurately define and solve recommendation challenges.# Ideal Candidate- We prefer candidates with experience in developing recommendation systems or predictive ranking models.- Candidates who have designed and improved machine learning models for predicting user responses, like CTR and CVR, will be highly regarded.- Experience in experimenting, tuning, and analyzing models using various features is a plus.- Familiarity with major ML frameworks such as PyTorch, TensorFlow, and LightGBM is advantageous.- Candidates who have engaged deeply in problem definition and performance analysis beyond merely training models are welcome.- Strong communication skills and the ability to think data-driven while articulating complex problems clearly are essential.# Resume Tips- Detail any impactful projects you have undertaken that influenced your organization significantly.- Explicitly describe the problems you defined, the approaches you selected, and the methods you used in modeling-centered projects.- Highlight any quantitative problem-solving processes you have engaged in through iterative experimentation and performance analysis.# Journey to Join TossApplication > 1st Technical Interview (Coding) > 2nd Technical Interview > Cultural Fit Interview > Reference Check > Offer Negotiation > Final Acceptance- The first technical interview will include a simple coding test, resume review, and ML fundamentals assessment.- The second technical interview will focus on in-depth technical discussions and ML system design.# A Note for Potential Colleagues> "This role goes beyond mere modeling; it makes an impact in business."- The most fulfilling aspect of working at Toss is that we do much more than just modeling.- Previously, my tasks were limited to inputting data into existing models for performance evaluation, but now I am engaged in integrating unaggregated data into models and contributing to impactful solutions based on user understanding for our super app!