Machine Learning Engineer - Robotics, Platforms for Vision Language Action Foundation Models
Company: Toyota Research Institute
Location: Los Altos
Posted on: April 1, 2026
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Job Description:
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 $253,000/year for
California-based roles. Base pay offered will depend on multiple
individualized factors, including, but not limited to, a
candidate's experience, skills, job-related knowledge, and market
location. 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. We may use artificial intelligence (AI)
tools to support parts of the hiring process, such as reviewing
applications, analyzing resumes, or assessing responses. These
tools assist our recruitment team but do not replace human
judgment. Final hiring decisions are ultimately made by humans. If
you would like more information about how your data is processed,
please contact us.
Keywords: Toyota Research Institute, Manteca , Machine Learning Engineer - Robotics, Platforms for Vision Language Action Foundation Models, IT / Software / Systems , Los Altos, California