Senior Machine Learning Platform Engineer at Coinbase | Remote - USA

Join Waymo as a Senior Machine Learning Engineer focusing on Perception LLM/VLM. In this role, you will leverage cutting-edge machine learning techniques to enhance our autonomous driving technology. You will collaborate with a talented team of engineers and researchers to develop algorithms that improve our perception systems, ensuring safety and efficiency on the road.

Join Us in Building a Safer World.At TRM Labs, we specialize in blockchain analytics and AI solutions aimed at assisting law enforcement, national security agencies, financial institutions, and cryptocurrency businesses in identifying, investigating, and preventing crypto-related fraud and financial crime. Our innovative platforms leverage blockchain intelligence and AI technology to trace funds, detect illicit activity, and construct comprehensive threat profiles. Trusted by leading organizations worldwide, TRM Labs is committed to enabling a safer and more secure environment for all.Our AI Engineering Team is dedicated to pioneering next-generation AI applications, particularly in the realm of Large Language Models (LLMs) and agentic systems. Our goal is to develop resilient pipelines and high-performance infrastructure that facilitate the swift, safe, and scalable deployment of AI systems.We manage extensive petabyte-scale pipelines, ensuring model serving with millisecond latency while providing the necessary observability and governance to make AI production-ready. Our team actively evaluates and integrates leading-edge tools in the LLM and agent space, including open-source stacks, vector databases, evaluation frameworks, and orchestration tools to accelerate TRM’s innovation pace.As a Senior or Staff ML Systems Engineer – LLM, you will play a pivotal role in constructing and scaling our technical infrastructure for AI/ML systems. Your responsibilities will include:Creating reusable CI/CD workflows for model training, evaluation, and deployment, integrating tools such as Langfuse, GitHub Actions, and experiment tracking.Automating model versioning, approval processes, and compliance checks across various environments.Developing a modular and scalable AI infrastructure stack that encompasses vector databases, feature stores, model registries, and observability tools.Collaborating with engineering and data science teams to embed AI models and agents into real-time applications and workflows.Continuously assessing and incorporating state-of-the-art AI tools (e.g., LangChain, LlamaIndex, vLLM, MLflow, BentoML).Promoting AI reliability and governance while enabling experimentation, ensuring compliance, security, and continuous uptime.Enhancing AI/ML Model Performance and ensuring data accuracy and consistency, leading to improved model training and inference.Implementing infrastructure to facilitate both offline and online evaluation of LLMs and agents.

Join gleanwork as a Machine Learning Engineer specializing in LLM evaluations and observability. In this role, you will be instrumental in developing cutting-edge machine learning systems that enhance our understanding and effectiveness of language learning models. You will collaborate with cross-functional teams to drive the integration of advanced analytics and machine learning solutions.

Bland Inc. seeks a Machine Learning Researcher specializing in Multimodal Large Language Models (LLMs) to join the team in San Francisco. The focus is on advancing AI systems that integrate language with other types of data. Role overview This position centers on research and development aimed at improving how AI models process and understand information from multiple sources, such as text combined with images or other modalities. What you will do Investigate how language interacts with additional data types within multimodal LLMs Create and evaluate new methods to enhance AI model performance Work closely with colleagues on projects designed to push the boundaries of machine learning Location This role is based in San Francisco.

At Scale AI, we are the premier partner for data and evaluation in the rapidly evolving field of artificial intelligence. Our commitment to advancing the assessment and benchmarking of large language models (LLMs) positions us at the forefront of AI innovation. We are dedicated to creating leading-edge LLM evaluation methodologies that set new benchmarks for model performance. Our research teams collaborate with the top AI laboratories in the industry to provide high-quality data, accelerate progress in generative AI research, and inform what excellence looks like in this domain. As a Staff Machine Learning Research Scientist on our LLM Evals team, you will spearhead the creation of novel evaluation methodologies, metrics, and benchmarks to assess the strengths and weaknesses of cutting-edge LLMs. Your work will shape our internal strategies and influence the broader AI research community, making this role essential for establishing best practices in data-driven AI development.

Company Overview:At Specter, we are pioneering a software-defined control plane for the physical realm, beginning with safeguarding American enterprises through comprehensive monitoring of their physical assets.Our innovative approach leverages a connected hardware-software ecosystem built on advanced multi-modal wireless mesh sensing technology. This breakthrough enables us to reduce the deployment costs and time for sensors by a factor of 10. Our ultimate goal is to establish a perception engine that provides real-time visibility of a company’s physical environment and facilitates autonomous operations management.Co-founders Xerxes and Philip are dedicated to empowering our partners in the rapidly evolving landscape of physical AI and robotics. Join our dynamic and rapidly expanding team comprised of talents from Anduril, Tesla, Uber, and the U.S. Special Forces.Position Overview:We are seeking a Perception AI Engineer who will be instrumental in transforming sensor data pipelines into actionable insights for our clients.Key Responsibilities:Implement and deploy a range of deep-learning models, including vision, vision-language, and large language models, within our sophisticated distributed perception system.Design and scale a production-ready data collection, labeling, and model retraining platform.Lead the design of a multimodal software user interface.

Join Bright Machines as a Senior Robot Perception Engineer, where you will play a pivotal role in advancing our smart robotics technologies. You will be responsible for developing and optimizing perception algorithms that enhance the functionality and efficiency of our robotic systems.As part of our innovative team, you will collaborate with engineers and researchers to implement state-of-the-art solutions that drive automation in various industries. Your expertise will be crucial in refining our systems to adapt to complex environments and improve operational outcomes.

As a premier data and evaluation partner for cutting-edge AI firms, Scale AI is committed to enhancing the evaluation and benchmarking of large language models (LLMs). We are developing industry-leading LLM evaluations that set new benchmarks for model performance assessment. Our mission is to create rigorous, scalable, and equitable evaluation methodologies that propel the next evolution of AI capabilities.Our Research teams collaborate with top AI laboratories to provide high-quality data and expedite advancements in Generative AI research. As the Tech Lead/Manager of the LLM Evaluations Research team, you will guide a skilled team of research scientists and engineers dedicated to crafting and applying innovative evaluation methodologies, metrics, and benchmarks that assess the strengths and weaknesses of our advanced LLMs. This pivotal role involves designing and executing a strategic roadmap that establishes best practices in data-driven AI development, thus accelerating the development of the next generation of generative AI models in collaboration with leading foundational model labs.

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 Whatnot as an LLM Platform Engineer where you'll be at the forefront of developing and optimizing cutting-edge language models. In this role, you will collaborate with a dynamic team of engineers and data scientists to enhance our machine learning infrastructure and algorithms. Your contributions will directly impact the efficiency and effectiveness of our language understanding capabilities.

About Scale AI At Scale AI, we are dedicated to propelling the advancement of AI applications. Over the past eight years, we have established ourselves as the premier AI data foundry, supporting groundbreaking innovations in fields such as generative AI, defense technologies, and autonomous vehicles. Following our recent Series F funding round, we are intensifying our efforts to harness frontier data, paving the way toward achieving Artificial General Intelligence (AGI). Our work with enterprise clients and governments has enhanced our model evaluation capabilities, allowing us to expand our offerings for both public and private evaluations. About the ACE Team The Agent Capabilities & Environments (ACE) team, a vital part of Scale’s Research organization, unites customer-focused Researchers and Applied AI Engineers. Our primary mission is to conduct research on agent environments and reinforcement learning reward signals, benchmark autonomous agent performance in real-world contexts, and develop robust data programs aimed at enhancing the capabilities of Large Language Models (LLMs). We are committed to creating foundational tools and frameworks for evaluating models as agents, focusing on autonomous agents that interact dynamically with a wide range of external environments, including code repositories and GUI interfaces. About This Role This position sits at the cutting edge of AI research and its practical applications, concentrating on the data types necessary for the development of state-of-the-art agents, including browser and software engineering agents. The ideal candidate will investigate the data landscape required to propel intelligent and adaptable AI agents, steering the data strategy at Scale to foster innovation. This role demands not only expertise in LLM agents and planning algorithms but also creative problem-solving skills to tackle novel challenges pertaining to data, interaction, and evaluation. You will contribute to influential research publications on agents, collaborate with customer researchers, and partner with the engineering team to transform these advancements into scalable real-world solutions.

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.

Join Our MissionAt Aquabyte, we are dedicated to transforming the sustainability and efficiency of aquaculture. Our ambitious mission aims to enhance fish farming practices, promoting a healthier production of low carbon protein while addressing significant climate change challenges. As the fastest growing food-production sector globally, aquaculture stands at the forefront of technological innovation to ensure our oceans are harvested and preserved for future generations.We embrace diversity and are driven by our mission. If you find our vision compelling, we would love to connect with you.Our Innovative ProductPresently, we focus on empowering salmon farmers with insights into their fish populations, enabling eco-friendly decision-making. Utilizing custom underwater cameras, advanced computer vision, and machine learning, our technology quantifies fish weights, assesses health status, and formulates optimal feeding strategies in real-time. Our comprehensive product consists of on-site hardware for image capture, cloud-based data processing pipelines, and a user-friendly web application, presenting numerous exciting challenges across all aspects of our technology stack.Above all, Aquabyte prioritizes customer satisfaction. Our product development is guided by the needs of fish farmers, ensuring that we consistently deliver exceptional value.Role OverviewAs a Perception Engineer, you will be instrumental in developing and implementing cutting-edge sensing technologies for fish farms worldwide. While our current offerings leverage underwater cameras and computer vision for assessing fish health and growth, we are expanding our sensor capabilities to create a holistic understanding of the underwater ecosystem.

Join Arcade as a Senior Machine Learning Engineer, where you'll be at the forefront of AI innovation. In this pivotal role, you will leverage advanced machine learning algorithms to create and enhance cutting-edge solutions. Collaborate closely with cross-functional teams to drive impactful projects from ideation to deployment.

Saris AI develops applied AI solutions for the banking sector, with teams in San Francisco, Montreal, and Toronto. The company builds automation tools that handle complex, long-context reasoning and agent-driven decision-making. Reliability and compliance shape every product, and Saris AI's agents already manage real customer workflows in production. As revenue grows, the engineering team is expanding to enhance current offerings and explore new directions. The Senior Machine Learning Engineer role is based in San Francisco and sits within the core engineering group. The team works in a collaborative, early-stage setting, balancing infrastructure needs with the delivery of features that serve customers directly. What you will do Build and maintain machine learning infrastructure, such as evaluation frameworks, prompt management systems, and tools for model observability. Develop new AI features for customers while supporting and improving the underlying infrastructure. Shape strategies for evaluation, LLM routing, prompt engineering, and model selection. Set practical standards to boost quality without slowing down development. Guide technical direction by clarifying trade-offs and architectural choices. Requirements Minimum 4 years of experience in machine learning or AI engineering, including production deployment of ML systems. Direct experience with large language models, prompt engineering, evaluation techniques, and model routing. Background in building tools and systems that deliver value to users. Comfort making pragmatic trade-offs and recognizing when a solution is sufficient. Ability to navigate ambiguity, define problems, and deliver results independently. Strong focus on end users and understanding the impact of ML decisions on customer experience. Supports team growth through code reviews, collaboration, and clear technical communication. Bonus Experience in regulated industries, especially banking.

Highlight is pioneering a shared intelligence framework for the contemporary workforce. Our solution integrates context across every member and tool in your team, effectively eliminating information silos. As your organization evolves, Highlight adapts by intelligently routing knowledge and reliably automating workflows.The RoleWe are seeking a Senior Machine Learning Engineer to contribute to the development of the AI systems that drive Highlight's operations. This position involves working across the entire ML stack, including data pipelines, model training, retrieval, ranking, evaluations, and deployment. You will deliver features that create a seamless experience for our users. This is a hands-on individual contributor role where you will manage critical systems from inception to deployment, collaborating closely with our Head of AI Engineering to enhance our ML capabilities.You will excel in this role if you are passionate about delivering production-ready ML systems, maintaining high standards of output quality, and tackling complex problems that have a tangible impact on users. We prioritize speed, uphold rigorous standards, and believe in the merit of ideas, regardless of hierarchy.Note: This is an on-site position, requiring five days a week at our San Francisco or New York City offices.ResponsibilitiesDesign, develop, and refine ML pipelines for context retrieval, action detection, and output generation.Implement and iterate on Retrieval-Augmented Generation (RAG) systems, ranking models, and prompt engineering to enhance quality.Establish comprehensive evaluations and monitoring frameworks to assess and enhance ML system performance.Explore alternative models and fine-tuning strategies for our substantial background processing workloads, creating improved systems that enhance quality while optimizing cost efficiency.Work in collaboration with Backend and Product Engineering teams to deliver AI-powered features.Influence ML infrastructure decisions and establish best practices across the engineering organization.Stay updated on advancements in LLMs, retrieval techniques, and ML tools; share insights with the team.Candidate ProfileWe are looking for an individual who is excited about crafting the AI user experience for the future. We value extreme ownership, accountability, and proactivity as we strive to exceed expectations. The ideal candidate is a skilled craftsman who enjoys developing exceptional products utilizing LLMs at scale.You are a suitable candidate if you possess:4+ years of experience in ML/AI engineering, with substantial involvement in deploying production systems.

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.