Senior Machine Learning Engineer - Applied Research Science

Join Our Team at MacroscopeAt Macroscope, we are dedicated to being the definitive source of truth for any software development company. Our mission is to empower leaders with clarity and provide engineers with the time they need to innovate.We enable leaders to gain insights into the evolution of their products and codebases—tracking changes, understanding team contributions, and identifying progress—all grounded in the ultimate source of truth: the code itself.Founded by experienced entrepreneurs who have successfully built and sold multiple companies, and held executive positions in public tech firms, we are backed by top-tier venture capital firms such as Lightspeed Venture Partners, Thrive Capital, Google Ventures, and Adverb.The RoleWe are seeking a Senior Applied Machine Learning Engineer who will be responsible for designing, developing, and optimizing the ML and AI systems that drive our core offerings. You will have full ownership of the systems, overseeing everything from data collection and evaluation to model experimentation and large-scale production deployment.This cross-functional position entails leading the ML/AI lifecycle for one of our most vital features: AI Code Review. Collaborating closely with our co-founders, you will make pivotal decisions that shape our product's development—ranging from building high-quality datasets to interpreting experimental results and enhancing model performance architecture. Additionally, you will play a significant role in crafting and implementing software that seamlessly integrates our models with our backend applications and user experience, offering a unique opportunity to influence our product's evolution significantly.Technology Stack: Typescript/React (frontend), Golang (backend), Temporal, Google Cloud (GCP), Postgres, Terraform, and custom-built AST "code walkers" in several programming languages including Golang, Typescript, Swift, Python, and Rust.

Join us at Foxglove, where we are revolutionizing the robotics industry by building robust data infrastructure for real-world applications.As robotics transitions from research environments to practical implementations in factories, warehouses, vehicles, and field operations, data becomes essential for engineers to troubleshoot failures, understand unexpected behaviors, and enhance robotic systems.At Foxglove, we provide the observability, visualization, and data infrastructure that enable robotics and autonomous systems teams to efficiently ingest, store, query, replay, and analyze extensive volumes of multimodal sensor data from live systems and production fleets.About the RoleWe are seeking a talented Applied Machine Learning Engineer with strong infrastructure insights to design, deploy, and scale the machine learning systems that power our data platform. In this impactful role, you will be responsible for optimizing production ML infrastructure—from enhancing inference pipeline throughput to establishing training and evaluation workflows. You will focus on high-priority challenges, such as developing retrieval applications for petabyte-scale multimodal robotics data, utilizing cutting-edge models to create high-performance search and data mining products, and fostering an internal ML flywheel for rapid iteration. This is a hands-on, application-driven position rather than a research-focused role.Key ResponsibilitiesDeploy and manage inference infrastructure for production ML workloads, focusing on model serving, scalability, and cost efficiency.Build and oversee vector database integrations and embedding applications to facilitate semantic search across various multimodal robotics data types (image, video, point cloud, and time series).Design and implement evaluation and training infrastructure to enhance model performance rapidly.Lead cloud architecture decisions and tools to optimize inference latency, throughput, cost, and reliability at scale.Collaborate closely with product engineers to deliver application-driven ML features that empower developers at the forefront of robotics and physical AI, steering clear of prototype experiments.Identify appropriate off-the-shelf solutions for production and determine when to build versus buy.

About UsAt Applied Compute, we specialize in creating Specific Intelligence solutions for enterprises, developing agents that learn continuously from an organization’s processes, data, expertise, and objectives. We recognize a significant gap between the capabilities of AI models in isolation and their practical applications in real-world business contexts. Our systems often fall short because they lack adaptability to feedback. To address this, we are building a continual learning infrastructure that captures context, memory, and decision-making processes throughout the enterprise, enabling specialized agents to effectively execute real tasks.What Excites Us: We operate at a unique intersection where our product team constructs the platform that fuels a new generation of digital coworkers. Our research team pushes the boundaries of post-training and reinforcement learning, creating innovative product experiences. Our applied research engineers collaborate closely with clients to deploy models into production. This blend of strong product focus, deep research, and hands-on customer engagement is crucial for integrating AI into the enterprise. We are product-driven, research-informed, and actively engaged with our clients.Our Team: Our diverse team consists of engineers, researchers, and operators, many of whom are former founders. We have built RL infrastructure at leading organizations like OpenAI and Scale AI, and developed systems at Together, Two Sigma, and Watershed. We proudly serve Fortune 50 clients alongside companies like DoorDash, Mercor, and Cognition. Our work is supported by renowned investors, including Benchmark, Sequoia, and Lux.Who Thrives in Our Environment: We seek individuals eager to apply cutting-edge research and complex systems to tackle real-world challenges. You should be adept at quickly adapting to new environments, whether it’s a fresh codebase, a client’s data architecture, or an unfamiliar problem domain. A genuine enjoyment of customer interactions—listening, empathizing, and understanding how tasks are accomplished within their organizations—is essential. Those with entrepreneurial backgrounds, extensive side projects, or demonstrated end-to-end ownership typically excel in our company.

P-1380 Join Databricks as a Senior Applied AI Engineer, where you will harness the power of machine learning, scheduling, and optimization algorithms to enhance the efficiency and performance of our engineering systems and infrastructure. Our Applied AI team tackles some of the most challenging and fascinating issues in the industry, ensuring that Databricks infrastructure and products operate at peak performance and cost efficiency. This role is critical, as our customers depend on us to deliver the most optimized workloads. Your Impact: Develop comprehensive systems from the ground up within a dynamic team of seasoned professionals. Influence the direction of our applied machine learning investment areas by collaborating with engineering and product teams across the organization. Lead the design and implementation of advanced AI models and systems that enhance the capabilities and performance of Databricks' products, infrastructure, and services. Architect and deploy robust, scalable machine learning infrastructure, including data storage, processing, model training, serving components, and monitoring systems to facilitate seamless integration of AI/ML models into production environments. Explore innovative modeling techniques in the realm of machine learning for systems. Contribute to the wider AI community by publishing research, presenting at conferences, and actively engaging in open-source projects, thereby strengthening Databricks' reputation as an industry leader.

Join David AIAt David AI, we are pioneering the audio data research landscape. Our research and development approach to data ensures that we deliver datasets with the same precision and rigor that leading AI labs apply to their models. Our mission is to seamlessly integrate AI into everyday life, leveraging audio as a key channel. As we witness advancements in audio AI and the emergence of new use cases, we recognize that high-quality training data is the critical component. This is where David AI steps in.Founded in 2024 by a group of former engineers and operators from Scale AI, we have rapidly established partnerships with major FAANG companies and AI labs. Recently, we secured a $50M Series B funding round from prominent investors including Meritech, NVIDIA, Jack Altman (Alt Capital), Amplify Partners, and First Round Capital.Our team is sharp, humble, and ambitious. We are on the lookout for talented individuals in research, engineering, product management, and operations to join us in our mission to redefine the audio AI landscape.About Our Machine Learning TeamOur Machine Learning team operates at the forefront of innovative research and practical application, transforming raw audio into high-quality data for top AI labs and enterprises. We manage the entire machine learning lifecycle—from exploring novel speech processing algorithms to deploying models that handle terabytes of audio data daily.Your RoleAs an Applied ML Engineer at David AI, you will develop state-of-the-art speech and audio models, establish production inference systems, and create robust pipelines that demonstrate the true potential of high-quality data.Key ResponsibilitiesResearch and Design: Create solutions using advanced signal processing algorithms and cutting-edge ML models tailored for speech and audio applications.Development: Build production-grade inference algorithms, pipelines, and APIs in collaboration with cross-functional teams to extract valuable insights for our clients.Collaboration: Work alongside our Operations team to gather valuable training and evaluation datasets to enhance our model quality.Architecture: Design systems that ensure durable and resilient inference and evaluations.

SentiLink is at the forefront of delivering cutting-edge identity and risk management solutions, providing both individuals and institutions the ability to transact with assurance. We are revolutionizing identity verification within the United States, replacing outdated, inefficient, and costly practices with solutions that are ten times faster, smarter, and more precise.Our rapid growth is a testament to our innovative approach; our real-time APIs have successfully verified hundreds of millions of identities, initially focusing on the financial sector and quickly expanding into various new markets. SentiLink enjoys the support of prestigious investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.We are proud to have received accolades from TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, and American Banker, and we have been featured in the Forbes Fintech 50 list every year since 2023. Notably, we made history as the first company to deploy the eCBSV and have testified before the United States House of Representatives regarding the future of identity verification.SentiLink accommodates a flexible work environment, ranging from fully remote positions to in-office roles. As a digital-first company, we emphasize collaboration across teams in the U.S. and India. We have physical locations in Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., alongside offices in Gurugram (Delhi) and Bengaluru in India. For those near our offices, we encourage regular office attendance. Certain roles, such as our engineering team in India, are designed to be primarily in-office.Role Overview:As a Senior Applied ML Scientist at SentiLink, you will be instrumental in developing our core products: advanced models aimed at identifying fraudulent activities while enhancing our expanding array of financial risk solutions. Your expertise as a seasoned researcher will be essential, making you the authoritative figure in your domain. You will frequently engage in high-impact projects that necessitate a profound understanding of the field, critical analytical skills, and robust technical capabilities. Collaboration with various teams across the organization will be key as you investigate new fraud types, innovate product offerings, and conduct analyses to support our sales and marketing efforts.

About Nooks.ai:Nooks is a cutting-edge AI Sales Assistant Platform (ASAP) designed to streamline sales processes, allowing representatives to concentrate on building relationships and closing deals. Our innovative platform has empowered thousands of sales professionals to achieve their targets, saving clients countless hours and generating substantial revenue. Trusted by sales teams at industry leaders like Hubspot, Rippling, and Toast, Nooks is transforming the sales landscape.Backed by over $70M in investments from top-tier venture capital firms, including Kleiner Perkins, Nooks has experienced remarkable growth, achieving a 4x and 3x increase in ARR over the past two years. We are on an ambitious trajectory to triple our growth once again this year.For more information, visit Nooks.ai.The RoleNote: Job title will be aligned with candidate experience.We are seeking a passionate Applied Machine Learning Engineer to join our dynamic team, tackling exciting technical challenges in the emerging field of AI-powered real-time collaboration. This role is pivotal in integrating machine learning features into the Nooks platform. The ideal candidate will have hands-on experience in a business where machine learning plays a central role.Key responsibilities will involve training production models to enhance their accuracy for specific sales applications, while aligning our technical strategy with performance, cost, and feasibility factors.Examples of Engineering Challenges You Might EncounterThese examples are illustrative; prior experience in all areas is not required. We hope you find some of these challenges intriguing!Real-time Audio AI & Precision/Recall/Latency Trade-offs (Algorithms & Models)Utilizing audio data, transcription, silence detection, and multiple signals to discern if a live call is a voicemail, a human, or a dial tree. Managing latency alongside precision/recall trade-offs is crucial for prompt human detection, involving advanced techniques like LLM embeddings, few-shot learning, data labeling, and continuous performance monitoring.Intelligent Call Funnels & Playbooks (Data Wrangling, Backend Engineering, GPT-3, UX)Analyzing the conversational flow to optimize call funnels and playbook strategies, focusing on data visibility and user experience.

About UsAt Speak, our mission is to revolutionize language learning.Learning a new language can transform lives by unlocking opportunities in diverse cultures, careers, and communities. With over two billion individuals around the globe striving to learn a language, we recognize that traditional one-on-one tutoring remains difficult to access at scale and has seen little innovation over recent decades. Speak is pioneering an AI-driven, human-level tutor accessible right from your pocket, providing a conversation-first experience where learners can practice speaking, receive immediate feedback, and progress through meticulously crafted lessons. Our goal is to facilitate a comprehensive journey from beginner to proficient speaker across various languages.Launched in South Korea in 2019, Speak has quickly become the leading language learning app in the region, now reaching learners across numerous markets and offering instruction in 15+ languages. Supported by over $150 million in venture capital from prestigious investors such as OpenAI, Accel, Founders Fund, and Khosla Ventures, our team is distributed across San Francisco, Seoul, Tokyo, Taipei, and Ljubljana.Role OverviewWe are seeking a skilled Machine Learning Engineer specializing in speech to join our innovative team. In this role, you will take charge of the entire modeling pipeline for speech recognition, encompassing training, experimentation, deployment, and ongoing monitoring. Collaborating closely with Product teams, you will design cutting-edge learning experiences and assess the effectiveness of production models on our users. As part of a nimble and dynamic team, you'll contribute as both a developer and a thought partner on projects related to ASR, assessments, pronunciation improvements, content personalization, and more. This is an exhilarating opportunity to be part of an ML team focused on crafting personalized learning experiences that will transform language education for millions worldwide.

We are seeking a talented Applied Machine Learning Engineer with a comprehensive understanding of the generative media landscape. You should possess an up-to-date knowledge of emerging methodologies and be capable of identifying gaps in the current market. Your role will involve innovating and developing machine learning models that enhance user experiences, requiring both novel training techniques and the fine-tuning of existing models with fresh datasets.

Founded in 2009 in the heart of Silicon Valley by visionaries Marc Andreessen and Ben Horowitz, Andreessen Horowitz (commonly known as a16z) is a premier venture capital firm dedicated to supporting innovative entrepreneurs who are shaping the future through technology. We pride ourselves on being stage agnostic, investing in technology companies from seed to venture and growth stages across diverse sectors including AI, bio + healthcare, consumer, crypto, enterprise, fintech, games, and initiatives contributing to American dynamism. Currently managing $90B across multiple funds, a16z is at the forefront of technological innovation.Our team is characterized by a profound respect for entrepreneurs and the intricate process of building companies; we understand the founder's journey firsthand. Our portfolio boasts industry leaders such as Anduril, Airbnb, Coinbase, Cursor, Databricks, Deel, Figma, GitHub, Roblox, SpaceX, and Stripe. We are committed to empowering founders and their teams to make a significant impact on the world.

Join Perplexity as an Applied Machine Learning Engineer and be at the forefront of innovation in artificial intelligence. You will design, develop, and refine advanced AI models that enhance user experiences globally. Your expertise in machine learning will allow you to create scalable solutions for user personalization, query comprehension, and content discovery, catering to the curiosity of millions.Key ResponsibilitiesUtilize cutting-edge ML and LLM techniques to address challenges in:Personalization (LLM memory, context summarization, retrieval, and ranking);Query Understanding (intent modeling, rewriting, agentic decomposition);Content Discovery (feed ranking and surfacing).Conduct thorough evaluations of LLM/ML models through offline and online methods, designing comprehensive experiments and metrics that yield insights into quality and impact.Manage the full model lifecycle from research to deployment, including data analysis, modeling, evaluation, A/B testing, and iterative enhancements.Collaborate with cross-functional teams, including engineers, PMs, data scientists, and designers, to ensure AI implementations yield significant product enhancements.Stay updated on ML/AI advancements by assessing and integrating new research and algorithms into the product lifecycle.Preferred QualificationsOver 5 years of experience in developing and deploying robust ML/AI models for large-scale, user-centric or data-driven applications.Extensive knowledge in deep learning frameworks (PyTorch, TensorFlow, JAX), LLMs, information retrieval, content summarization, recommendation systems, NLP, and ranking.Proficient software engineering skills (Python, production-level codebases, collaborative development).Comprehensive experience across the entire ML lifecycle: data analysis, feature engineering, model development, evaluation, and ongoing monitoring/improvement.Effective collaborator and communicator; thrives in fast-paced, cross-functional environments.Inquisitive, motivated by user/product impact, and passionate about advancing applied ML and AI.Bachelor's, Master's, or PhD in Computer Science, Engineering, or a related field (or equivalent experience).

SentiLink is at the forefront of transforming identity verification and risk management, enabling both institutions and individuals to conduct transactions with confidence. We are committed to revolutionizing the outdated and inefficient identity verification landscape in the United States, offering solutions that are ten times faster, more intelligent, and more precise.Our rapid growth reflects the significant traction we've garnered, with our real-time APIs successfully verifying hundreds of millions of identities, especially within the financial services sector, while swiftly expanding into other markets. SentiLink enjoys the backing of top-tier investors such as Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.We have received accolades from major publications including TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, and American Banker, and have consistently ranked on the Forbes Fintech 50 list since 2023. Notably, we made history by being the first company to implement the eCBSV and provided testimony before the United States House of Representatives regarding the future of identity verification.SentiLink promotes a flexible working environment, offering various work arrangements ranging from fully remote to in-office. As a digital-first organization, we emphasize strong collaboration across teams in the U.S. and India. Our offices are located in cities including Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., along with Gurugram (Delhi) and Bengaluru in India. If you are near any of these locations, we encourage regular in-office engagement. Some positions are designed to be hybrid or in-office. For instance, our engineering team in India primarily operates from our Gurugram office.

The OpportunityJoin us at ComfyOrg as a Senior/Staff Applied Machine Learning Engineer! We are on the hunt for a passionate innovator who is enthusiastic about optimizing model inference. You will play a pivotal role in developing the heart of ComfyUI, our cutting-edge visual AI platform. Your expertise will help us push the limits of AI model performance, making them run faster and more efficiently than ever before.Are You a Match?You are fascinated by model inference, memory management, and torch optimizations.You possess experience in writing production-level PyTorch code that challenges performance standards.You have a passion for understanding the inner workings of AI models.You thrive on developing highly optimized code that consistently delivers results.You believe that the current landscape of ML deployment holds significant room for improvement.Your Responsibilities:Develop and enhance the core inference engine that drives ComfyUI.Optimize large models for speed and memory efficiency.Collaborate with our core team to architect new features.Tackle complex technical challenges within the visual AI domain.Contribute to the future direction of our technology.Experience with diffusion or LLM models, as well as creating custom nodes for ComfyUI, is highly beneficial.

About UsAt Applied Compute, we are pioneering the development of Specific Intelligence for enterprises, creating agents that continuously learn from a company’s processes, data, expertise, and objectives. Our mission is to bridge the gap between isolated AI capabilities and their effective application within real business environments. Traditional AI systems often fall short as they lack the ability to adapt based on feedback. Our innovative continual learning layer captures context, memory, and decision-making processes across the enterprise, enabling specialized agents to engage in meaningful work.What Excites Us: We operate at the exciting intersection of product development and cutting-edge research. Our product team designs the platform that empowers a new generation of digital coworkers, while our research team drives advancements in post-training and reinforcement learning to enhance user experiences. As an applied research engineer, you will work directly with clients to implement models in production, combining robust product development with deep research insights to facilitate AI integration in enterprises.Meet Our Team: Our diverse team consists of engineers, researchers, and operators, many of whom are former founders. We have previously built reinforcement learning infrastructure at OpenAI, established data foundations at Scale AI, and contributed to significant systems at companies like Together, Two Sigma, and Watershed. We collaborate with Fortune 50 clients, including DoorDash, Mercor, and Cognition, and are proud to be backed by reputable investors such as Benchmark, Sequoia, and Lux.Who Thrives Here: We seek individuals who are passionate about applying innovative research and complex systems to solve real-world challenges. You should feel comfortable navigating new environments rapidly—be it a fresh codebase, a client’s data architecture, or an unfamiliar problem domain. A genuine enjoyment for customer interaction, empathy, and a deep understanding of their operational workflows are essential. Candidates with entrepreneurial backgrounds, extensive side projects, or a proven track record of end-to-end ownership typically excel in our environment.

About NationGraphAt NationGraph, we are revolutionizing the accessibility and usability of public sector data for businesses targeting municipalities, state agencies, educational institutions, and specialized districts. Our advanced data intelligence engine extracts actionable insights from millions of public sector sources, empowering organizations to make informed decisions. Established in 2024, our mission is to democratize information, ensuring that public data is genuinely accessible to everyone. Discover more at nationgraph.comOur TeamComprises seasoned entrepreneurs who have successfully built, scaled, and exited multiple companies.Developed robust software infrastructure capable of processing billions in transactions.Supported by top-tier venture capitalists and seasoned operating partners with a track record of investing in and nurturing iconic brands.Role OverviewDesign and implement end-to-end machine learning pipelines.Extract and mine data from various online sources through large-scale web crawling and scraping techniques to enhance our models and insights.Convert unstructured text data into structured knowledge using natural language processing (NLP), entity recognition, and bespoke models.Develop and refine text classification models to systematically organize intricate datasets.Enhance retrieval-augmented generation (RAG) systems utilized in our product offerings.Drive our data strategy by identifying and integrating new data sources.Tackle open-ended technical challenges, fostering a culture of learning and collaboration within the team.Primarily utilize Python and SQL for development.QualificationsA strong quantitative background in fields such as computer science, physics, mathematics, or engineering.Solid foundation in mathematics and statistics.A PhD in a quantitative discipline.Expertise in Python programming.Proactive ownership mentality with the ability to address complex technical challenges to create commercial value.A genuine enthusiasm for continuous learning, growth, and uncovering insights from complex datasets.Strong problem-solving, communication, and collaboration abilities in a dynamic work environment.

Join our innovative Match Team as a Senior Machine Learning Engineer at Enigmaio, where you will play a pivotal role in developing advanced algorithms and models that enhance our matching capabilities. You will collaborate with cross-functional teams to design, implement, and optimize machine learning solutions that drive business outcomes.

About Taskrabbit:Taskrabbit is an innovative marketplace platform that seamlessly connects individuals with Taskers to manage everyday home tasks, including furniture assembly, handyman services, moving assistance, and much more.At Taskrabbit, we aim to transform lives one task at a time. We celebrate innovation, inclusion, and hard work, fostering a collaborative, pragmatic, and fast-paced culture. We seek talented, entrepreneurially minded, data-driven individuals who possess a passion for empowering others to pursue their passions. In partnership with IKEA, we are creating more opportunities for individuals to earn a consistent, meaningful income on their terms by establishing enduring relationships with clients in communities globally.Taskrabbit operates as a hybrid company, with team members located across the US and EU, and has been recognized as a Built In — Best Places to Work for 2022, 2023, and 2024, receiving accolades across various national and regional categories. Join us at Taskrabbit, where your contributions will be significant, your ideas appreciated, and your potential maximized!This position operates on a hybrid schedule, requiring two days of in-office collaboration per week. It can be based in our San Francisco office or our new New York City office (opening March 2026).About the RoleMachine Learning is a foundational element at Taskrabbit, and we are in search of an experienced Senior Machine Learning Engineer to join our team and help mold the future of ML/AI at Taskrabbit. This distinct, full-stack role is designed for someone who is enthusiastic about the entire machine learning lifecycle—from initial research and model development to constructing the robust infrastructure necessary for deploying and scaling your innovations.As a Senior Machine Learning Engineer, you will engage with exciting challenges that directly influence how users discover and interact with home services on the Taskrabbit platform. You will play a vital role in enhancing our capabilities in areas such as search ranking, content discovery, and recommendation systems. Collaborating closely with data scientists and fellow engineers, you will design and implement cutting-edge algorithms, ensuring the scalability, reliability, and optimization of our models in production alongside software engineers.

About VSCO At VSCO, we empower photographers with an innovative platform that provides essential tools, a vibrant community, and the visibility needed for creative and professional growth. We cultivate an authentic creative environment that welcomes photographers of all skill levels, offering a space that inspires opportunity, collaboration, and connection. Our mission is to support photographers in their journeys, enabling them to thrive and connect with fellow creatives and businesses through our comprehensive suite of tools, available on both mobile and desktop. We seek individuals who are passionate and proactive in advancing our mission. Our team members have the opportunity to make a significant impact, and we believe that collaborative efforts yield stronger results. Our core values are essential to our team culture and guide our hiring process. Learn more about what you can expect when joining VSCO on our Careers Page. About The Role As a Senior Machine Learning Engineer, you will harness the power of AI and machine learning to create innovative, reliable user-facing product features. You will leverage your extensive technical background and hands-on experience in deploying machine learning models to deliver impactful solutions based on real-world feedback. Your focus on measurable outcomes and customer satisfaction drives your work, blending innovation with practical implementation. You will be highly skilled in Python and adept across the data and machine learning stack, enabling you to develop and launch models efficiently while ensuring scalability and maintainability. Whether working with traditional algorithms or cutting-edge deep learning and generative AI, you will expertly navigate the complexity of each problem, managing every phase from defining the challenge to deployment and iterative improvement. Your dedication to software engineering excellence will inform your thoughtful approach to system design for machine learning, encompassing data quality, pipeline design, feature workflows, model serving, and ongoing monitoring and enhancement. By integrating machine learning deeply within our cohesive product experiences, you will collaborate effectively with cross-functional teams, aligning on objectives, defining success metrics, and driving meaningful outcomes. You will stay informed about the rapidly evolving AI landscape, maintaining a discerning perspective that allows your team to focus on significant advancements while avoiding distractions. The Day to Day Design and implement ML-powered features for search, discovery, personalization, and more.

Join Orchard as a Machine Learning Engineer and play a pivotal role in transforming data into actionable insights. In this dynamic position, you will leverage your expertise in machine learning algorithms and data analysis to develop innovative solutions that enhance our products and services.We are looking for a proactive team player who thrives in a fast-paced environment and possesses strong problem-solving skills. You will collaborate with cross-functional teams, engage with large datasets, and contribute to the design and implementation of machine learning models.