Senior Machine Learning Researcher at Toyota Research Institute

Los Altos, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Automotive, Autonomous Vehicles, Artificial IntelligenceIndustries

Requirements

Strong track record of leading independent research efforts
Experience with machine learning techniques
Preferred experience mentoring and collaborating with less experienced students and researchers
Expertise in generative AI (e.g., diffusion policy)
Familiarity with large-scale sensor data processing
Understanding of imitation learning and large-scale data

Responsibilities

Conduct ambitious research to advance the state-of-the-art in using generative AI for end-to-end perception, planning, and prediction in automated driving
Research and implement scalable end-to-end architectures that process raw sensor data to generate vehicle trajectories
Prototype, validate, and iterate model architectures using imitation learning and large-scale data
Explore data quality filtering, transfer learning from diverse data sources, and edge deployment optimization
Integrate visual-language-action modalities
Contribute to refining models for closed-loop driving on public roads and in simulation
Explore long-tail driving scenarios with low data coverage
Support Toyota’s global AI efforts to build a more coordinated global approach across Toyota entities

Skills

Machine Learning

Generative AI

Diffusion Policy

Imitation Learning

Large-Scale Sensor Data Processing

End-to-End Perception

Planning

Prediction

Automated Driving

ADAS

Large Behavior Models

Transfer Learning

Edge Deployment

Visual-Language-Action Models

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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