Machine Learning Engineer - Imitation & Reinforcement Learning for Robotics

Be Part of the Future of Autonomous RoboticsAt Bedrock Robotics, we are pioneering the transition of AI from theoretical frameworks to practical applications in the built environment. Our team is comprised of seasoned professionals who have been instrumental in the success of innovative companies such as Waymo, Segment, and Uber Freight. We are at the forefront of deploying autonomous technologies in heavy construction machinery, significantly enhancing the efficiency and safety of multi-billion dollar infrastructure projects across the nation.With backing from $350 million in funding, our mission is to address the urgent need for housing, data centers, and manufacturing facilities, while simultaneously responding to the construction industry's labor shortages.This position is where cutting-edge algorithms meet the practical world of construction. You will work alongside industry experts and top-tier engineers to tackle complex real-world challenges that cannot be simulated. If you are eager to leverage advanced technology for impactful problem-solving within a skilled team, we encourage you to apply.

Join the forefront of technology as we revolutionize the construction industry with advanced autonomy.Be a Part of Innovation at Bedrock RoboticsAt Bedrock Robotics, we are transforming artificial intelligence from theoretical concepts into practical applications that enhance the world’s infrastructure. Our team comprises seasoned professionals who have been pivotal in launching industry leaders like Waymo, scaling Segment to a $3.2 billion acquisition, and driving Uber Freight to $5 billion in revenue. We are currently implementing autonomous systems in heavy construction machinery nationwide, expediting the timelines of multi-billion dollar infrastructure developments while significantly enhancing job site safety.With a robust funding of $350 million, we are rapidly addressing the escalating demand for housing, data centers, and manufacturing facilities, all while tackling the construction sector's increasing labor shortages. This is where innovative algorithms meet the realities of heavy machinery.If you are passionate about leveraging cutting-edge technology to tackle real-world challenges and wish to collaborate with a talented team of industry experts, we invite you to apply.Role: Machine Learning Engineer: EvaluationBedrock Robotics is on a mission to integrate autonomy into construction processes! We are seeking a driven engineer with substantial experience in evaluating complex machine learning systems in real-world scenarios. Your objective will be to convert the intricate dynamics of the built environment into actionable, AI-driven evaluations that enhance the adoption of our Bedrock Operators.The ideal candidate will have a proven track record in developing evaluation systems and executing statistical analyses to assess performance variations across system iterations. Your experience in iterating on complex machine learning systems in production environments will be crucial, as you navigate the intricacies involved.Your Responsibilities:Design and Maintain Evaluation Systems:Develop and maintain pipelines for performance measurement—encompassing both open-loop and closed-loop simulations, hardware-in-the-loop systems, and field data from Bedrock Operator-equipped machinery. Collaborate with other teams to glean insights earlier in the development cycle through optimized workflows.Develop Metrics:Align product objectives with system behaviors by translating real-world specifications into measurable indicators derived from logged data. Enable data-driven decision-making for everything from parameter adjustments to strategic program planning.

At Scale AI, our Physical AI division is at the forefront of addressing data challenges in Robotics, Autonomous Vehicles, and Computer Vision. We invite you to join our team as a Machine Learning Systems Engineer, where you will play a pivotal role in applied research and the development of machine learning pipelines. Your focus will be on enhancing algorithms and pipelines for optimal performance on cloud-based GPU systems, empowering advancements in Physical AI research and applications.Your Role:As a Machine Learning Systems Engineer within the Physical AI team, you will design and implement robust platforms that ensure the scalable and efficient deployment of foundational models for physical agents. Your contributions will support groundbreaking research and production systems, facilitating internal discoveries and external applications in the fields of robotics and autonomous technology.We seek candidates who possess a strong foundation in machine learning coupled with extensive backend system design expertise. You will thrive in a collaborative environment, bridging the gap between Physical AI research and production engineering to expedite innovation across Scale AI.

About the RoleIn this exciting position, you will address comprehensive challenges to enhance the performance of our AI models deployed on robotic systems. Your responsibilities will include adding new features to our video processing data pipeline, updating our machine learning data loaders, training models to validate your modifications, and testing these changes in real-world robotic applications. This role requires the integration of numerous distributed Python services to achieve specific data processing and application tasks, alongside managing substantial cloud infrastructure for efficient business logic processing at scale.Your responsibilities will include:Conceptualizing and implementing innovative solutions to enhance system robustness, scalability, and speed.Revamping existing systems and services to accommodate significant future growth.Developing business logic to ensure our robots access the necessary data and that customers receive appropriate access to our robotic solutions.You may excel in this role if you:Possess extensive experience in building complex distributed applications or data pipelines at scale.Have a background in processing petabytes of data, especially video data.Demonstrate expertise in Python, with foundational knowledge in distributed infrastructure and solid understanding of modern machine learning principles.Have a robust foundation in contemporary ML techniques with experience in large-scale ML training and production deployments.Have familiarity with distributed cloud infrastructure and a deep understanding of cloud networking, permissions, and container orchestration (Kubernetes).About GeneralistAt Generalist, our mission is to realize the potential of general-purpose robots. We envision a future where industries and homes thrive on the collaboration between humans and machines. Our robots are designed to enhance productivity and efficiency.We focus on developing embodied foundation models, starting with dexterity, which necessitates pushing the boundaries of data, models, and hardware to enable robots to intelligently interact with their environments.Our company is deeply rooted in large-scale AI and robotics, with a team drawn from leading organizations like OpenAI, Boston Dynamics, and Google DeepMind, all committed to delivering groundbreaking advancements in AI technology.

Join us at Physical Intelligence as a Research Scientist, where you will be at the forefront of innovation in machine learning and robotics. We are in search of exceptional researchers across all experience levels who demonstrate a strong track record of impactful research results. Ideal candidates will possess a solid foundation in both practical implementation and theoretical frameworks, showcasing a blend of system-building capabilities and significant conceptual, algorithmic, or theoretical advancements. We value diverse backgrounds and encourage applications from both traditional academic researchers and those with unique, unconventional experiences.We are committed to fostering a diverse and inclusive workplace. In accordance with the San Francisco Fair Chance Ordinance, we welcome applications from qualified individuals with arrest and conviction records.

About KreaKrea is at the forefront of developing advanced AI creative tools designed to enhance and empower human creativity. Our mission is to create intuitive and controllable AI solutions that allow creatives to express themselves across various formats including text, images, video, sound, and 3D.About the PositionWe are seeking a talented Machine Learning Engineer to lead the design and implementation of Krea’s personalization and recommendation systems from the ground up. You will take full ownership of how we comprehend user preferences, curate engaging content, and customize generative models to reflect individual aesthetics.This role sits at the exciting intersection of recommendation systems, representation learning, and generative imaging and video technologies.Your ResponsibilitiesLead the architecture and development of Krea’s personalization and recommendation framework, overseeing the technical direction from inception to deployment.Craft algorithms that effectively model user preferences and tastes, enabling our systems to adapt to individual styles and aesthetics.Develop high-quality, curated feeds that strike a balance between exploration, personalization, and aesthetic coherence.Collaborate closely with our model and research teams to co-create personalization mechanisms that shape how our generative models learn, adapt, and express creative styles.Contribute to research in personalized image generation, with a focus on style, taste, and subjective quality.Work in tandem with product, design, and research teams to define what “good personalization” means in a creative context.Take systems from initial research and prototyping stages through to production, ongoing iteration, and enhancement.

Are you passionate about the intersection of robotics and artificial intelligence? We are seeking a Robot Learning Generalist to join our innovative team. In this role, you will leverage your expertise to develop and implement advanced learning algorithms that enhance robotic capabilities. You will collaborate with a diverse group of engineers and researchers to push the boundaries of what robots can achieve in real-world scenarios.As a part of our team, you will have the opportunity to work on cutting-edge projects that have a tangible impact on the future of robotics. Your contributions will help shape the development of intelligent systems that can learn from their environment and adapt to new challenges.

Join Scale AI's ML platform team (RLXF) as a Machine Learning Research Engineer, where you will play a pivotal role in developing our advanced distributed framework for training and inference of large language models. This platform is vital for enabling machine learning engineers, researchers, data scientists, and operators to conduct rapid and automated training, as well as evaluation of LLMs and data quality.At Scale, we occupy a unique position in the AI landscape, serving as an essential provider of training and evaluation data along with comprehensive solutions for the entire ML lifecycle. You will collaborate closely with Scale's ML teams and researchers to enhance the foundational platform that underpins our ML research and development initiatives. Your contributions will be crucial in optimizing the platform to support the next generation of LLM training, inference, and data curation.If you are passionate about driving the future of AI through groundbreaking innovations, we want to hear from you!

About Physical Intelligence Physical Intelligence is building general-purpose AI for the physical world. The team brings together engineers, scientists, roboticists, and entrepreneurs focused on foundational models and learning algorithms for robots and interactive devices. Role Overview The Robotics Research Engineer works at the intersection of hardware, software, and large-scale model training. The goal: develop efficient autonomous robot policies that move the field forward. What You Will Do Design robotic systems and data collection pipelines to generate high-quality training data Develop learning algorithms that turn collected data into reliable, effective robot policies Contribute to vision-language-action models, from concept through implementation Help shape datasets, research infrastructure, and the direction of robotics research at Physical Intelligence Location San Francisco

Join xdof at a pivotal moment as we lead the charge in the development of general-purpose robotics. With frontier labs racing to create advanced robotic systems, high-quality training data is a critical challenge. Our mission is to build the essential infrastructure that supports foundational models – from data collection systems and operational capabilities to an exabyte-scale data warehouse and innovative software toolchains. This will empower our partners to advance the field of robotics.As a Research Engineer, you will be at the forefront of designing, constructing, and deploying real-world robotic learning systems. Your work will encompass manipulation, locomotion, and control, transitioning robots from raw hardware to fully operational systems.This hands-on position requires you to take ownership of systems from inception to deployment on actual robots. You will play a crucial role in establishing the technical foundations that facilitate large-scale robotic learning.

Join Anthropic as a Machine Learning Systems Engineer within our Encodings and Tokenization team, where you'll play a pivotal role in refining and optimizing our tokenization systems across Pretraining and Finetuning workflows. By bridging the gap between our Pretraining and Finetuning teams, you will help shape the essential infrastructure that enhances how our AI models learn from diverse data. Your contributions will be crucial in ensuring our AI systems remain reliable, interpretable, and steerable, driving forward our mission of developing beneficial AI technologies.

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.

The Bot CompanyWe are on a mission to create a helpful robot for every household.Our dynamic team of engineers, designers, and operators is headquartered in San Francisco, featuring talent from renowned companies such as Tesla, Cruise, OpenAI, Google, and Pixar. We have a proven track record of delivering exceptional products to hundreds of millions of users.Our lean structure fosters swift decision-making and minimizes bureaucracy, empowering every team member with significant autonomy and responsibility. We embrace a culture of rapid iteration and execution across the tech stack.What We Seek in CandidatesAt The Bot Company, we value sharp minds capable of thriving in fast-paced, high-pressure environments. Candidates should exhibit:Exceptional Mental Acuity: The ability to think quickly, assimilate new information instantly, and make connections across various domains.Engineering Curiosity: A natural inclination to explore and understand how systems function, even beyond your specialized area.High Performance Mindset: Comfort with rapid movement, adeptness in handling ambiguity, and excellence under demanding conditions.Role Overview: ML Compiler EngineerAs a specialist in developing ML compilers for edge devices (custom silicon and others), you will be pivotal in establishing a robust deployment framework to efficiently execute large neural networks on our robots with minimal latency.Key QualificationsProficient coding skills with extensive experience in C++ and/or Python.Familiarity with modern compiler infrastructure (MLIR/LLVM, XLA, TVM, Glow, etc.).Experience in deploying models on heterogeneous computing platforms (preferably edge devices).Proficiency in writing kernels (CUDA/OpenCL).Knowledge of quantization techniques is advantageous, though not mandatory.Your ResponsibilitiesDesign, develop, and maintain compiler infrastructure tailored for our hardware.Collaborate across teams, including ML and Systems Software.Independently diagnose and resolve complex numerical issues (such as discrepancies between training and inference) while enhancing performance.

Join us in creating the backbone of data infrastructure for real-world robotic operations.As robotics transitions from research labs to real-world applications across factories, warehouses, vehicles, and field deployments, understanding the intricacies of robotic performance becomes critical. When robots encounter failures or unexpected behaviors, data analysis is key to deciphering the underlying issues.At Foxglove, we are at the forefront of building tools for observability, visualization, and data infrastructure that empower robotics and autonomous systems teams to manage, analyze, and derive insights from vast amounts of multimodal sensor data collected from operational systems and production fleets.Role OverviewWe are seeking a passionate ML Platform Engineer with robust infrastructure expertise to design, deploy, and scale our data platform systems. This platform-centric role will allow you to take charge of the infrastructure layer that facilitates machine learning in production environments, going beyond just the models themselves.Your responsibilities will encompass ensuring the reliability, scalability, and performance of the ML platform, including areas such as inference serving, pipeline orchestration, training infrastructure, and evaluation frameworks. You will be tackling substantial challenges such as managing petabyte-scale multimodal robotics data and optimizing high-throughput retrieval and embedding pipelines in a hands-on infrastructure capacity.Key ResponsibilitiesDesign and operationalize production inference infrastructure, focusing on model serving, autoscaling, load balancing, and cost efficiency across cloud environments.Own the platform architecture for embedding and retrieval pipelines that enable semantic search across multimodal robotics data (image, video, point cloud, and time series).Develop and sustain the training and evaluation infrastructure that supports rapid model performance iteration, including job orchestration, experiment tracking, and dataset versioning.Lead decisions on cloud infrastructure (AWS/GCP) that affect latency, throughput, reliability, and scalability.Establish platform abstractions and internal tools that empower product engineers to deliver ML-enhanced features without managing infrastructure directly.Assess, integrate, and operationalize third-party ML infrastructure components while establishing clear build vs. buy frameworks for the team.

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.

About Our TeamJoin the innovative Sora team at OpenAI, where we are at the forefront of developing multimodal capabilities for our foundation models. Our hybrid research and product team is dedicated to seamlessly integrating multimodal functionalities into our AI solutions, ensuring they are dependable, user-centric, and aligned with our vision of benefiting society at large.Role OverviewAs a Machine Learning Engineer specializing in Distributed Data Systems, you will be instrumental in designing and scaling the infrastructure that facilitates large-scale multimodal training and evaluation at OpenAI. Your role will involve managing complex distributed data pipelines, collaborating closely with researchers to convert their requirements into robust, production-ready systems, and enhancing pipelines that are essential for Sora's rapid iteration cycles.We are seeking detail-oriented engineers with extensive experience in distributed systems who thrive in high-stakes environments and excel in building resilient infrastructure.This position is located in San Francisco, CA, and follows a hybrid work model, requiring three days in the office each week. We also provide relocation assistance for new team members.Key Responsibilities:Design, implement, and maintain data infrastructure systems, including distributed computing, data orchestration, distributed storage, streaming infrastructure, and machine learning systems, with a focus on scalability, reliability, and security.Ensure our data platform can scale exponentially while maintaining high reliability and efficiency.Collaborate with researchers to gain a deep understanding of their requirements, translating them into production-ready systems.Strengthen, optimize, and manage critical data infrastructure systems that support multimodal training and evaluation.You Will Excel in This Role If You:Possess strong experience with distributed systems and large-scale infrastructure, coupled with a keen interest in data.Exhibit meticulous attention to detail and a commitment to building and maintaining reliable systems.Demonstrate solid software engineering fundamentals and effective organizational skills.Thrive in environments characterized by ambiguity and rapid change.About OpenAIOpenAI is a trailblazing AI research and deployment organization committed to ensuring that general-purpose artificial intelligence serves humanity. We continuously push the boundaries of AI capabilities and strive to create technology that benefits everyone.

At Philo, we are a dedicated team of technology and product enthusiasts committed to reshaping the television landscape. We blend cutting-edge technology with the captivating medium of television to create the ultimate viewing experience. Our mission is to enhance streaming capabilities through innovative cloud delivery and sophisticated machine learning algorithms that personalize content discovery. As a Senior Machine Learning Engineer specializing in Recommendation Systems, you will be at the forefront of our content personalization initiatives, significantly enhancing user engagement and satisfaction. Your expertise will help ensure that every time users open the Philo app, they find something they want to watch. In this pivotal role, you will spearhead the development of advanced algorithms and large-scale systems that drive Philo's recommendation engine. Collaborating closely with data science, product, infrastructure, and backend engineering teams, you will tackle complex machine learning challenges and develop innovative, data-driven solutions that enhance content discovery and foster user retention.

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.

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 Ando Technologies as a Machine Learning Engineer specializing in AI-native systems and forecasting. In this role, you will leverage cutting-edge machine learning algorithms to develop predictive models and enhance our AI-driven solutions. Collaborate with cross-functional teams to transform data into actionable insights and drive strategic decisions. Ideal candidates will have a passion for innovation and a strong understanding of AI technologies.