Automated Driving Advanced Development Intern, Machine Learning Research at Toyota Research Institute

Los Altos, California, United States

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Not SpecifiedCompensation

InternshipExperience Level

InternshipJob Type

UnknownVisa

Automotive, Autonomous Driving, AI ResearchIndustries

Requirements

Currently pursuing a Ph.D. or equivalent experience in Computer Science, Robotics, Engineering, or a related field
Proficiency in Python for implementing and evaluating research ideas
Experience with ML frameworks such as PyTorch
Understanding of version control, testing, and software engineering fundamentals
Passion for collaborative engineering and building reliable ML systems that support real-world autonomy

Responsibilities

Conduct ambitious research to advance the state-of-the-art in using new capabilities in generative modelling for end-to-end planning from vision in automated driving
Implement scalable end-to-end architectures that process raw sensor data to generate vehicle trajectories, addressing the challenges of long-tail driving scenarios with low data coverage
Prototype, validate, and iterate on model architectures using imitation learning, and large-scale data, ensuring robust performance across diverse scenarios
Perform closed-loop evaluations in sensor simulations and real-world testing environments
Explore multi-modal and language-conditioned models to broaden the applicability of end-to-end policies, leveraging external data sources and transfer learning to enhance generalization

Skills

Machine Learning

End-to-End ML

Perception

Planning

Control

Simulation

Systems Engineering

Deployment

Pixels to Trajectories

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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