Software Engineer II - Machine Learning Feature Platform

Join our cutting-edge team at Afresh Technologies as a Staff Software Engineer specializing in Machine Learning Platforms. In this fully remote position, you will play a pivotal role in designing, building, and optimizing our ML infrastructure to support innovative solutions that redefine the food supply chain. Your expertise will help us harness the power of machine learning to drive efficiency and sustainability in food distribution.

Join Afresh Technologies as a Senior Software Engineer and play a critical role in enhancing our Machine Learning Platform. This is an exciting opportunity to work on cutting-edge technology in a fully remote environment. You will collaborate with data scientists and engineers to build scalable machine learning solutions that drive innovation and improve efficiency in food supply chains.

Narvar is expanding and seeking a talented Senior Software Engineer II to innovate and enhance our platform. At Narvar, data is integral to our success, enabling you to make a significant impact on our organization, partners, and end users. As a Machine Learning Engineer at Narvar, you will engage in full-stack development, crafting production-level code and managing machine learning operations for diverse teams. Key Responsibilities Design and implement machine learning algorithms applicable to e-commerce, consumer behavior, market analysis, logistics, and innovative product development. Analyze real-world consumer data utilizing natural language processing, image classification, time series analysis, outlier detection, and user modeling. Handle large volumes of unstructured data effectively. Bridge the disciplines of mathematics, machine learning, business, and computer science to influence millions of users with your contributions. Enhance the capabilities of the data science team by developing frameworks, tools, and methodologies that are leveraged by the entire team. Provide strategic guidance to the team through high-quality documentation, code reviews, and a strong vision that reflects both practical experience and broader industry insights.

Join Elastic as a Principal Software Engineer II specializing in Machine Learning and Elasticsearch, where you'll lead advanced projects and innovate solutions for our clients. You will work with a talented team of engineers and contribute to the development of state-of-the-art applications that leverage machine learning algorithms and Elasticsearch capabilities. This is an opportunity to shape the future of search technology and make a significant impact within our organization.

Greetings, Future Homie!Join us at Homebase, where we are passionate about empowering small businesses to flourish. Our dynamic team is driven by empathy, urgency, and a bold approach that leads to meaningful outcomes. At Homebase, every team member contributes to elevating our standards, supporting each other, and celebrating our collective successes.We are not merely developing an application; we are fostering unstoppable teams. Are you ready to join us?Your Impact Begins HereAs a Platform Engineer, you will play a key role in designing and implementing components for our data and ML platforms. Your contributions will empower data engineering, data science, and product teams to create features driven by data and machine learning, ensuring that our systems are scalable, reliable, and seamlessly integrated.Architect, develop, and enhance the ingestion processes for large volumes of both structured and unstructured data from a variety of sources.Facilitate data architecture transformation initiatives on Databricks, promoting scalable and efficient systems.Lead the design and implementation of platform components for training, deploying, and monitoring machine learning models in production environments.Provide insights into industry best practices, tools, and technologies in the field of machine learning engineering.Champion continuous enhancements of data and ML workflows through automation and innovative solutions.Own projects end-to-end, ensuring successful delivery from planning to execution.Collaborate with cross-functional teams to gather business requirements and develop effective technical solutions. Key to Your Success - These experiences and strengths will position you for success:Over 5 years of experience in software development, with a focus on data and machine learning.Proficient in SQL, Python, and Databricks.Experience with Airflow, Kafka, and Redshift.Strong skills in data modeling and database design.Expertise in building and deploying machine learning models, including language models.Experience in creating model serving pipelines for batch, streaming, and real-time inference.Demonstrated ability to work collaboratively in a fast-paced environment.

About the Role Movable Ink is hiring a Senior Platform Engineer with a focus on Machine Learning for its Toronto office. This role centers on building and improving machine learning features within our marketing technology platform. What You Will Do Work closely with colleagues from different teams to design and implement machine learning solutions that strengthen the platform. Develop and maintain systems that help clients deliver personalized experiences to their audiences at scale. Apply engineering expertise to create reliable, maintainable, and scalable ML infrastructure. Location This position is based in Toronto at Movable Ink.

Join Mistplay, the leading loyalty application for mobile gamers, as we redefine the gaming experience! Our platform connects millions of enthusiastic mobile players, allowing them to discover exciting new games while earning rewards for their time and investment. Players can redeem these rewards for gift cards, making gaming more rewarding than ever. Our mission is to provide the ultimate mobile gaming experience for everyone, everywhere!We are currently seeking a Senior / Staff Platform Engineer, ML & Data to join our dynamic team. In this role, you will report to the Vice President of Data and Machine Learning Platform, playing a crucial role in developing and enhancing our data architecture and machine learning capabilities.

About FaireFaire is an innovative online wholesale marketplace that champions the local economy. We believe that independent retailers worldwide can outpace major corporations like Walmart and Amazon, even if they are smaller entities in comparison. At Faire, we harness technology, data, and machine learning to empower a vibrant community of entrepreneurs globally. Think of your favorite local boutique; we facilitate their access to the finest products from around the world, enabling them to thrive in their neighborhoods. By providing the right tools and insights, we aim to level the playing field, allowing small businesses to effectively compete with e-commerce giants.By nurturing independent businesses, Faire is fostering positive economic growth in local communities worldwide. We are on the lookout for intelligent, resourceful, and passionate individuals to join our mission of promoting the shop local movement. If you believe in community and collaboration, we invite you to be part of ours.About this RoleAs a Senior Staff Machine Learning Platform Engineer, you will be responsible for shaping the technical vision and progression of Faire’s ML platform. Your role will include setting standards, influencing organization-wide architecture, and leading complex, cross-functional initiatives to enhance data science efficiency on a large scale. Additionally, you will play a crucial role in adapting ML workflows to leverage contemporary AI productivity tools. Your work will not only involve building models but also architecting the systems that empower those models to support tens of thousands of small retailers in growing their local businesses.

Role overview Aerovect is looking for a Machine Learning Operations Software Engineer to join the team in Toronto. The position centers on building and deploying machine learning models that support the company’s products. The main focus is on refining workflows, maintaining model reliability, and contributing to the team’s results. What you will do Develop and maintain systems that handle the deployment of machine learning models Collaborate with engineers and data scientists to improve and streamline machine learning processes Help ensure the performance and reliability of Aerovect’s product offerings Location This role is based in Toronto.

Join Mistplay, the leading loyalty app for mobile gamers, as a Senior Machine Learning Platform / Infrastructure Engineer II. At Mistplay, our vibrant community of millions of mobile gamers engages with our platform to discover new games and earn valuable rewards. Players are compensated for their time and investment in gaming, redeeming these rewards for gift cards. Our mission is to enhance the mobile gaming experience for everyone, everywhere! Download Mistplay on the Google Play Store here and connect with us on Instagram, Twitter and Facebook.Important Note: In Canada , Mistplay operates under a hybrid model, requiring 2 days per week in-office presence in Toronto (400 University Ave) & Montreal (1001 Blvd. Robert-Bourassa).

Tiger Analytics is seeking a talented and forward-thinking Senior Machine Learning Engineer with extensive hands-on experience in Google Cloud Platform (GCP) and Vertex AI. In this pivotal role, you will be responsible for designing, building, and deploying scalable machine learning solutions, while operationalizing ML models and managing the complete ML lifecycle from data ingestion to model serving and monitoring.Key Responsibilities: Develop, train, and optimize machine learning models utilizing Vertex AI, leveraging Vertex Pipelines, AutoML, and custom model training techniques. Design and construct scalable ML pipelines for feature engineering, model training, evaluation, and deployment. Deploy models to production via Vertex AI endpoints and ensure seamless integration with downstream applications or APIs. Collaborate closely with data scientists, data engineers, and MLOps teams to foster reproducible and dependable ML workflows. Monitor model performance, establish alerting systems, retraining triggers, and drift detection mechanisms. Utilize GCP services such as BigQuery, Dataflow, Cloud Functions, Pub/Sub, and GCS throughout ML workflows. Apply CI/CD principles to ML models using Vertex AI Pipelines, Cloud Build, and GitOps practices. Implement model governance, versioning, explainability, and security best practices within Vertex AI. Document architectural decisions, workflows, and model lifecycles clearly for internal stakeholders.

At d-Matrix, we are pioneering the potential of generative AI to transform the technology landscape. Positioned at the cutting edge of both software and hardware innovation, we continuously strive to expand the horizons of what can be achieved in this dynamic field. Our workplace culture is built on the principles of respect and collaboration.We emphasize the importance of humility and open communication. Our inclusive team thrives on diverse perspectives, which lead to innovative solutions. We are on the lookout for motivated individuals who are passionate about overcoming challenges and are driven by tangible outcomes. Are you ready to explore your playground? Together, we can unlock the infinite possibilities of AI.Job Title: Software Engineering Intern - KernelsLocation: Toronto, CanadaProgram Duration: 12 weeks: June 1st - August 21st or June 22nd - September 11thProject Overview:As a Software Engineering Intern on our Kernels team, you will have a significant impact on the development of high-performance kernels that are crucial for accelerating machine learning models. Your role will encompass creating reference implementations for accuracy verification, defining unit tests for the implemented operators, optimizing performance, conducting scalability analysis across varying problem sizes, and packaging and shipping the final implementations. You will also gather performance metrics and identify bottlenecks to enhance core functionality.What You Will Do:Implement high-performance kernels using low-level languages (Assembly/ISA experience is a plus).Develop, test, and optimize kernels for machine learning models and performance.Automate the creation of reference implementations and unit tests.Analyze scalability and performance, collect metrics, and troubleshoot bottlenecks.Package and share implementations with partner teams.

Wisedocs is an innovative and rapidly expanding AI platform that revolutionizes the way insurance companies evaluate claims. With approximately $20 million USD in funding, over 100 team members worldwide, and more than 90 clients across North America and Australia, we are experiencing remarkable growth, doubling our revenue year after year.Founded by industry experts who have firsthand experience with the claims process, Wisedocs merges extensive domain expertise with cutting-edge AI, trained on over 100 million documents. Our platform simplifies complex medical records into clear, structured insights, supported by expert human oversight.Join our mission-driven team dedicated to developing intelligent products that simplify complexity, expedite decision-making, and create a significant impact when it matters most.Role OverviewWe are on the lookout for a Senior Machine Learning Engineer to spearhead the scaling and innovation of machine learning initiatives across the organization. In this pivotal role, you will enhance our inference and training pipelines to accommodate a higher volume of customers while refining extraction and summarization techniques across various modalities. You will foster a customer-centric approach and collaborate with fellow senior engineers to seamlessly integrate the ML system into the broader Wisedocs platform.Our Current ML EcosystemWe have three primary types of ML systems operational in production: an entity classification system, a custom reports generator, and a series of summarization models. Our entity classification has been functioning for four years and currently processes data asynchronously using a combination of models. Discover more about our initiatives at our tech blog.Recent Projects by Our ML Team:Reconstructing our inference pipeline to achieve 100x scalingDeveloping consistent parsing methods for 50,000-page PDFsDeploying our pipeline within an isolated government client environmentYour ResponsibilitiesDesigning and implementing machine learning models to analyze and interpret large sets of medical and insurance documentsCreating robust, scalable APIs using PythonCollaborating with technical stakeholders and leaders to contribute to system design and implementationEnsuring the reliability and scalability of ML systems while enforcing best practices in data engineering and model lifecycle managementWorking closely with our expert-in-the-loop teams to develop industry-leading evaluationsAdditional responsibilities will evolve as projects progress and change

c-serv is forming an AI Red Team to improve the security of enterprise AI products. As an Adversarial Machine Learning Engineer, the focus will be on identifying vulnerabilities in large language model (LLM) systems and testing their defenses before they reach enterprise clients. This hands-on position addresses practical security challenges in real-world AI deployments. Main responsibilities Perform adversarial assessments targeting LLMs and other AI systems Simulate real-world attack scenarios, including: Prompt injection Jailbreaking and bypassing model guardrails Data exfiltration Model inversion and evasion Manipulation of retrieval-augmented generation (RAG) pipelines Develop scripts and tools to automate attack scenarios Evaluate model behavior and performance under adversarial conditions Identify weaknesses in technical components, such as: APIs Embedding pipelines Vector databases Fine-tuned model deployments Collaborate with engineering teams to verify fixes and improvements Document findings clearly and thoroughly Location This position is based in Calgary, Alberta, Canada. Impact The work in this role directly supports the reliability and security of AI systems before they are deployed at scale for enterprise use.

At StackAdapt, we are at the forefront of marketing technology, enabling marketers to precisely engage and convert their audiences. With an astounding 465 billion automated optimizations executed every second, our AI-driven StackAdapt Marketing Platform bridges the gap between brand and performance marketing, delivering measurable results throughout the customer journey. The most innovative marketers partner with StackAdapt to execute high-impact campaigns across diverse programmatic advertising and marketing channels.We are on the lookout for a Senior Software Engineer to become a vital member of our Stats & Analytics Data Platform team — the backbone of our extensive data infrastructure at StackAdapt. This team processes terabytes of data daily, catering to both real-time and batch processing needs. Our data platform guarantees the freshness, accuracy, and cost-effectiveness of data, ensuring that analytics, machine learning, and product teams can rely on trustworthy, governed datasets.As a remote-first company, StackAdapt welcomes candidates from all over the United States and Canada.

“Transform every logistics journey into a remarkable experience”Company Overview:Established in 2014, Quincus is a pioneering B2B SaaS platform specializing in supply chain operations, with its headquarters in Singapore. Our mission is to tackle the pressing challenges of global supply chains through innovative technology. By leveraging AI and machine learning, we have revolutionized the logistics landscape, providing our clients with unparalleled transparency and efficiency in their supply chain operations.Founded by two visionary entrepreneurs with over a decade of tech experience, Quincus is led by Chief Product Officer Katherina-Olivia Lacey, who champions a tech revolution while promoting women's empowerment within the supply chain sector. CEO Jonathan E. Savoir, recognized in Forbes' 30 Under 30 Asia List in 2020, also contributes to several startup boards, driving innovation forward.Role Overview:Quincus Research is at the forefront of developing the next generation of intelligent systems for our suite of products. We are seeking a highly motivated and skilled Machine Learning Engineer to join our dynamic team. You will play a pivotal role in designing and deploying deep learning and reinforcement learning algorithms at scale. Your expertise will be essential in creating scalable systems for model serving, optimizing inference performance, and managing production workflows.Key Responsibilities:- Design and implement scalable systems for deploying deep learning and reinforcement learning models.- Optimize the inference performance of models through advanced techniques like quantization, pruning, and distillation.- Leverage GPU computing to enhance model training and inference efficiency.- Develop and manage production workflows for the training and deployment of machine learning models.- Collaborate cross-functionally with data scientists and software engineers to create effective machine learning systems.- Monitor and enhance the performance of machine learning models in production.- Stay abreast of the latest advancements in deep learning and reinforcement learning methodologies.

Join Our Innovative TeamSanctuary AI is at the forefront of developing dexterity-driven Physical AI for versatile robots. We are on the lookout for talented Machine Learning Engineers to become part of our dynamic team of engineers, researchers, and scientists. Together, we are committed to overcoming significant challenges in robotic perception, dexterous manipulation, planning, and reasoning.In this role, you will concentrate on creating robust systems to train and implement machine learning policies in robotic platforms. You will collaborate closely with researchers to introduce and execute cutting-edge ML techniques in production environments. Utilizing our state-of-the-art in-house robotic systems, you will design, test, and enhance software that connects advanced methodologies to practical outcomes. This role presents a unique opportunity to contribute to both the engineering foundations and the applied ML capabilities that propel our robots into the future.Note: Your role may require occasional travel (typically one to two weeks at a time, several times a year) to work closely with partners and teams on essential projects.

Join bree as a Machine Learning Engineer, where you will be at the forefront of cutting-edge technology, developing algorithms and models that drive innovation. Collaborate with a dynamic team to enhance machine learning frameworks and contribute to impactful projects that transform data into actionable insights.

Affinity integrates billions of data points from extensive datasets to craft a precise and powerful depiction of the global professional relationship graph. Our users gain essential insights and visibility to cultivate and leverage opportunities within their teams' networks. The position is part of the AI Platform team, responsible for the AI services that drive Affinity's premier relationship intelligence platform. Our work involves extracting and retrieving information from vast amounts of structured and unstructured data to provide actionable insights to our clients. As a Senior Machine Learning Engineer, you'll collaborate closely with data engineers, software engineers, and product managers to shape the future of the leading CRM platform in private capital. Your role will involve designing and building AI systems that efficiently uncover insights from dynamic business interaction data—an exciting and unique opportunity within the sector. This position focuses on applied machine learning with a significant emphasis on engineering rather than research. You will be instrumental in enhancing our ML Engineering capabilities, specifically in information retrieval and ultimately in recommendation systems. Key Responsibilities: Own the full ML lifecycle: Guide projects from ideation to production, encompassing feature engineering, model selection, deployment, and model observability and evaluation. Translate business needs into ML solutions: Gather product requirements and convert them into robust ML system design specifications. Build recommendation and ranking systems: Architect and implement ranking and recommendation infrastructure from the ground up, initially leveraging integrated off-the-shelf models and evolving to tailored solutions over time. Solve complex problems: Tackle diverse challenges in information extraction, storage, and retrieval for both structured and unstructured data. Collaborate cross-functionally: Work alongside cross-functional teams (product, infrastructure, data engineering, and software engineering) to develop robust, high-scale systems that underpin our data processing and ML operations.