Responsibilities
- Build a visually realistic simulator to test full end-to-end autonomy stack behavior, from simulating sensors to motion planning, across a range of scenario conditions.
- Prototype and integrate with internal and third-party simulators to evaluate their ability to support learned system testing.
- Curate scenarios, system introspection.
- Build data logging frameworks used during large-scale virtual tests.
- Collaborate closely with autonomy, ML, and integration teams to define simulation entry points, runtime configs, and closed-loop evaluation metrics.
- Build diagnostic tooling and analysis pipelines to understand and improve real system behavior in simulation.
- Lead cross-functional efforts to close the gap between simulation and on-vehicle deployment, increasing the reliability of sim-based validation.
- Provide technical mentorship and foster a collaborative, high-trust engineering culture across organizational boundaries.
- Demonstrate excellent design practices; generate technical documentation; lead technical presentations; aligning with stakeholders before, during, and after implementation is essential.
Qualifications
- Bachelor’s or Master’s in Computer Science, Robotics, or a related field.
- 10+ years of experience in robotics, autonomous systems, or simulation.
- Experience with 3D reconstruction (e.g. Gaussian Splatting, Neural radiance fields, etc).
- Experience with 3D generation.
- Experience with Unreal Engine.
- Strong programming skills in Python and C++, especially for robotics or systems development.
- Experience with simulation platforms (e.g., CARLA, Applied Intuition, Nvidia DriveSim, etc) and their integration into autonomous system workflows.
- Knowledge of sensor simulation principles and how perception systems interact with synthetic data.
- Understanding of end-to-end autonomy pipelines, from raw sensor input to trajectory outputs.
- Demonstrated ability to design for both users (e.g., autonomy developers) and simulation infrastructure stakeholders.
- Passion for using simulation to drive real-world progress and system understanding.
Bonus Qualifications
- Hands-on experience validating machine learning-based autonomy stacks in closed-loop simulation.
- Knowledge of scenario generation, rare event simulation, or counterfactual testing.
- Knowledge of one or more cloud compute platforms, such as AWS.
- Experience with multi-agent simulation or high-fidelity 3D environments.
- Prior experience in fast-paced R&D environments bridging research and production.
Top Skills
What We Do
Toyota Research Institute (TRI) envisions a future where Toyota products, enabled by TRI technology, dramatically improve quality of life for individuals and society. To achieve its Vision, TRI’s Mission is to create new tools and capabilities focused on improving the human condition through research in Energy & Materials, Human-centered AI, Human Interactive Driving, and Robotics.
We’re on a mission to improve the quality of human life. To lead this transformative shift, we are looking for the world's best talent -- people who enjoy solving tough problems while having fun doing it.
Why Work With Us
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.
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