Machine Learning Engineer
Company: Toyota Research Institute
Location: Los Altos
Posted on: February 13, 2026
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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. The Automated Driving
Advanced Development division at TRI will focus on enabling
innovation and transformation at Toyota by building a bridge
between TRI research and Toyota products, services, and needs. We
achieve this through partnership, collaboration, and shared
commitment. This new division is leading a new cross-organizational
project between TRI and Woven by Toyota to conduct research and
develop a fully end-to-end learned driving stack. This cross-org
collaborative project is harmonious with TRI’s robotics divisions'
efforts in Diffusion Policy and Large Behavior Models. We are
looking for a Machine Learning Engineer to join our autonomy team
and help bring end-to-end ML models (from pixels to trajectories )
into robust, testable, and deployable systems. This role is ideal
for engineers who thrive at the intersection of machine learning,
systems engineering, and real-world deployment. You’ll contribute
to the implementation, evaluation, and integration of ML-based
components for perception, planning, and control. This includes
supporting our team’s efforts in simulation-based testing,
real-time deployment, and data-driven model development. You’ll
work closely with researchers, data engineers, and autonomy
engineers to ensure models scale from prototype to production. This
work is part of Toyota’s global AI efforts to build a more
coordinated global approach across Toyota entities.
Responsibilities Implement, maintain, and evaluate end-to-end ML
models used in the autonomy stack Collaborate with ML researchers,
data scientists and engineers, and simulation teams to build
training, evaluation, and deployment pipelines. Integrate models
into real-time systems running on simulation and vehicle platforms,
ensuring correctness and performance. Support open-loop,
closed-loop, and batch evaluation workflows of trained models,
including metrics tracking, ablation studies, and debugging tools.
Help design scalable workflows for managing large datasets (e.g.,
demonstration driving for imitation learning) and support diverse
scenario coverage. Write clean, modular, well-tested code with a
focus on reliability, clarity, and maintainability. Qualifications
Bachelor’s or Master’s degree in Computer Science, Robotics,
Engineering, or a related field. 3 years of strong experience with
ML frameworks such as PyTorch, Tensorflow or Caffe. Strong Python
and C++ programming skills and solid understanding of ML model
development best practices. Familiarity with metrics dashboards,
experiment tracking, and ML ops tooling (e.g., Weights & Biases,
MLflow, Metaflow). Some experience working with robotics or
real-world sensor data (e.g., video, lidar, IMU, or radar). Strong
understanding of version control, testing, and software engineering
fundamentals. Enthusiasm for collaborative engineering and building
reliable ML systems that support real-world autonomy. Bonus
Qualifications Experience working with ROS, simulation frameworks
(e.g., CARLA, Nvidia DriveSim), or vehicle interfaces. Experience
with model deployment with NVIDIA stack (e.g. ONNX graphs,
TensorRT, profiling) Exposure to distributed training, inference
optimization, or model deployment on edge devices. Familiarity with
recent breakthroughs in ML (e.g. foundation models, pre-training
and efficient fine-tuning, multimodal Transformer architectures).
Please include links to any relevant open-source contributions or
technical project write-ups with your application. 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 may vary depending on multiple individualized factors,
including, but not limited to, business or organizational needs,
market location, job-related knowledge, skills, and experience.
Note that TRI offers a generous benefits package (including 401(k)
eligibility and various paid time off benefits, such as vacation,
sick time, and parental leave) and an annual cash bonus structure.
Details of participation in 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, Fairfield , Machine Learning Engineer, IT / Software / Systems , Los Altos, California