Research Engineer, Simulation Robot Learning

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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics.

We’re on a mission to improve the quality of human life by creating robots that can learn, adapt, and assist in everyday environments. We are building a world-class team to push the boundaries of robot learning, combining machine learning, perception, prediction, and action to produce robust and coordinated robot behaviors.

We’re looking for a motivated Research Engineer to help develop the next generation of AI-powered robots through high-fidelity simulation and Large Behavior Models. In this role, you’ll work at the intersection of machine learning, computer vision, robotics, and physics-based modeling to enable scalable and generalizable robot policy development. Experience with simulation or embodied systems (robots, autonomous vehicles, etc.) is a strong plus.

As part of our team, you’ll contribute to cutting-edge research while leveraging TRI’s expertise in ML, cloud, software, and hardware to build systems that move from simulation to real-world deployment.

• Build, improve, and robustify end-to-end integrated ML pipelines for training multimodal (language, images, 3D, video, actions) models at scale.
• Develop and manage physics-based robot simulation environments enabling scalable training and evaluation of learning-based behavior models in realistic, physically grounded scenarios.
• Integrate and validate learned policies in simulation, assessing real-world applicability, generalization, and performance across diverse environments, tasks, geometries, and sensor viewpoints.
• Train, finetune, and serve robot foundation models with a strong MLOps mindset.
• Build processes for integrating collaboration-produced and open-source advancements and code into our internal stack.
• Collaborate with internal research scientists and our partner labs at top academic institutions and Toyota research labs to drive pioneering research at scale.

• Bachelor's or master's degree in Computer Science, Robotics, Physics, or a related field.
• 2+ years of professional engineering experience at an AI/ML-focused organization.
• Strong proficiency in Python and experience with simulation frameworks such as Isaac Sim, PyBullet, Mu Jo Co , or similar.
• Hands-on experience with robotics simulation, reinforcement learning, or large-scale machine learning.
• Familiarity with state-of-the-art methods in behavior learning and/or computer vision.
• Experience integrating ML models into simulated or real-world environments.
• Extensive practical experience with PyTorch.
• Ability to alternate between rapid prototyping and production-quality implementation.
• Solid understanding of software engineering best practices, including testing, CI/CD, and documentation.

• Experience deploying models on embodied systems/robots.
• Experience working in mixed teams of research scientists and engineers.
• Exposure to MLOps tools and infrastructure (e.g., Docker, EC2, S3, Sagemaker).

Please submit a brief cover letter and add a link to Google Scholar to include a full list of publications when submitting your CV for this position.

The pay range for this position at commencement of employment is expected to be between $128,000 and $192,000/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.

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