Robotics Machine Learning Engineer - Platforms for Vision Language Action Foundation Models

At Toyota Research Institute (TRI), we’re on a mission to improve the quality of human life. We’re developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we’ve built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences.

We are looking for a machine learning engineer to develop our infrastructure and support researchers in the development of foundation models for robotics.

The Mission
We are working to create general-purpose robots capable of accomplishing a wide variety of dexterous tasks. To do this, our team is building general-purpose machine learning foundation models for dexterous robot manipulation. These models, which we call Large Behavior Models (LBMs), use generative AI techniques to produce robot action from sensor data and human request. To accomplish this, we are creating a large curriculum of embodied robot demonstration data and combining that data with a rich corpus of internet-scale text, image, and video data. We are also using high-quality simulation to augment real world robot data with procedurally-generated synthetic demonstrations.

The Team
The Robotics Machine Learning Team’s charter is to push the frontiers of research in robotics and machine learning to develop the future capabilities required for general-purpose robots able to operate in realistic environments such as homes or factories.

The Job
We have several research thrusts under our broad mission, and we are looking for a machine learning engineer to contribute to some of the following objectives:

Hardware Infrastructure: Develop our hardware platform, making sure the robots and software stack are state-of-the-art, operational, and continuously improved with new functionalities. This includes the robot hardware (YAM, Franka, and custom), the sensors (monocular, stereo, depth, etc), the robot/computer interface, the human/robot interface, the data logging, and the controls.

Inference & Deployment: Build APIs and systems for high-throughput inference and logging in simulation and on real robot platforms. Enable low-latency model serving and robust policy–environment communication.

Evaluation & Monitoring: Design metrics pipelines for quantitative and qualitative evaluation. Build tools for experiment tracking, logging, visualization, and leaderboard management using systems like Weights & Biases, MLflow, or ClearML.

Data Infrastructure: Build scalable pipelines for heterogeneous multimodal data (images, text, video, touch, depth, proprioception). Work with data storage, versioning, streaming, and visualization systems optimized for throughput and accessibility.

The machine learning engineer who joins our team will be expected to create working code, and interact frequently with researchers. They will run experiments with both simulated and real (physical) robots, and participate in publishing the work to peer-reviewed venues. We’re looking for an engineer who is comfortable working with multiple robotic embodiments and stacks as well as a growing dynamic corpus of robot data.

Qualifications :
• Hardware experience on robots
• Communication protocol experience (ROS, WebSocket, RPC…)
• Strong software engineering skills in Python, PyTorch, and distributed systems.
• Experience with large-scale data handling, including streaming, preprocessing, and storage of video or sensor data.
• A “make it happen” attitude and comfort with fast prototyping.
• A passion for robotics and development grounded in important fundamental problems.
• Continuous integration

Bonus Qualifications :
• Familiarity with modern ML efficiency frameworks (e.g., FSDP, DeepSpeed, XLA, Ray, Hugging Face Accelerate).
• Experience with machine learning and familiarity with large multi-modal datasets and models.
• Experience working in a research environment, published research papers, open-source projects

The pay range for this position at commencement of employment is expected to be between $176,000 and $264,000/year for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, 401(k) eligibility, paid time off benefits (including vacation, sick time, and parental leave), and an annual cash bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer of employment.

Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information.

TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant’s race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.