Research Scientist, Trustworthy Learning under Uncertainty (TLU) - Large Behavior Models 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

Robotics, Artificial Intelligence, AutomotiveIndustries

Requirements

Strong background in embodied machine learning
Expertise in Policy Evaluation, Failure Detection and Mitigation, and Active Learning in the context of Large Behavior Models (LBMs) for robotic manipulation
Knowledge in areas such as Multi-Modal Foundation Models, Generative Modeling, Imitation Learning, Reinforcement Learning, Planning & Control, Statistics, Uncertainty Estimation, Out-of-Distribution Detection, Safety-Aware & Robust ML, (Inter)Active Learning, and Online / Continual Learning
Ability to conduct research independently and collaborate effectively as part of a research team
Experience with robots preferred, particularly in the manipulation domain
Driven personality with a “make it happen” mentality

Responsibilities

Work as part of a dynamic, closely-knit team conducting research on reliable, robust, and adaptive deployment of machine learning models in robot manipulation
Push the boundaries of state-of-the-art in trustworthy learning under uncertainty for large behavior models

Skills

Key technologies and capabilities for this role

Machine LearningDeep LearningRoboticsFoundation ModelsGenerative Deep LearningLarge-Scale Pre-trainingUncertainty Quantification

Questions & Answers

Common questions about this position

What is the employment type for this position?

This is a full-time position.

Is this role remote or does it require working on-site?

This information is not specified in the job description.

What expertise is required for this Research Scientist role?

The role requires a strong background in embodied machine learning, with specific expertise in Policy Evaluation, Failure Detection and Mitigation, and Active Learning in the context of Large Behavior Models.

What is the focus of the TLU team at Toyota Research Institute?

The Trustworthy Learning under Uncertainty (TLU) team within the Robotics division focuses on enabling the robust, reliable, and adaptive deployment of Large Behavior Models at scale in human environments through rigorous evaluation, failure detection and mitigation, and active/continual learning.

What makes a strong candidate for this research scientist position?

A strong candidate is a driven research scientist or engineer with a strong background in embodied machine learning and a 'make it happen' mentality, particularly with expertise in policy evaluation, failure detection, and active learning.

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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