Machine Learning Engineer - Robotics, Platforms for Vision Language Action Foundation Models
Company: Toyota Research Institute
Location: Los Altos
Posted on: February 13, 2026
|
|
|
Job Description:
Job Description 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
$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. 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, Elk Grove , Machine Learning Engineer - Robotics, Platforms for Vision Language Action Foundation Models, IT / Software / Systems , Los Altos, California