Senior Simulation Engineer at Toyota Research Institute

Los Altos, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Automotive, Artificial Intelligence, RoboticsIndustries

Requirements

Bachelor’s or Master’s in Computer Science, Robotics, or a related field
10+ years of experience in robotics, autonomous systems, or simulation
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) Hands-on experience validating machine learning-based autonomy stacks in closed-loop sim

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

Skills

Simulation Workflows

Sensor Simulation

System-Level Simulation

Closed-Loop Validation

Synthetic Data Generation

Data Pipelines

Autonomous Driving

Machine Learning Infrastructure

Robotics

Toyota Research Institute

Research in mobility, safety, and automation

About Toyota Research Institute

Toyota Research Institute focuses on improving mobility through research and development in the automotive and technology sectors. The company works on enhancing safety, automated driving, robotics, materials science, and machine learning. Their products include advanced safety features and automated driving systems that aim to make driving safer and more efficient. Unlike many competitors, TRI emphasizes a research-driven approach, collaborating with various partners and licensing their innovations to enhance Toyota's offerings and maintain a competitive edge. The goal of TRI is to advance mobility solutions that improve quality of life and support the transition to zero-emissions transportation.

Los Altos, CaliforniaHeadquarters

2016Year Founded

$100MTotal Funding

SEEDCompany Stage

Robotics & Automation, Automotive & Transportation, AI & Machine LearningIndustries

201-500Employees

Benefits

Highly competitive benefits package

Robust programs to support the wellbeing, happiness, and health of our people and their families.

401(k) plan including matching and annual profit sharing along with total vacation and holidays totaling 38 days per year.

Subsidized commuter benefits and generous employee and vehicle allowances

2 paid days per year to participate in volunteer activities.

Maternity Leave program with 10 paid weeks plus baby bonding leave and Milk Stork for traveling moms

Baby Bonding Leave–an additional 16 paid weeks–to all new parents, including those who choose to adopt.

Back-up child and adult / elder care programs to help everyone thrive

WellBeats Virtual Fitness Trainer.

Risks

Public skepticism may undermine AI-assisted driving safety initiatives.

Boston Dynamics' high costs could impact TRI's humanoid robot project returns.

Complexity of real-world environments may delay TRI's robot skill deployment.

Differentiation

TRI focuses on AI to enhance human life and mobility.

Partnerships with Boston Dynamics and Stanford showcase TRI's collaborative innovation.

TRI's Driving Sensei concept integrates AI to improve driver skills and engagement.

Upsides

Generative AI allows TRI's robots to learn complex tasks without new coding.

TRI's AI-driven material synthesis could revolutionize EV battery development.

Autonomous tandem drifting collaboration with Stanford pushes vehicle dynamics boundaries.

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