Research Engineer, Simulation for Robot Learning at Toyota Research Institute

Los Altos, California, United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Robotics, Automotive, AI ResearchIndustries

Requirements

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, MuJoCo, 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

Responsibilities

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

Skills

Machine Learning

Computer Vision

Robotics

Physics-based Simulation

ML Pipelines

Multimodal Models

Robot Foundation Models

Embodied AI

Policy Training

Simulation Environments

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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