Tri Source International

Tri Source International

Senior Machine Learning Researcher, Large Behavior Models & Diffusion Policy

Los Altos, CA · Senior

Sponsorship not specifiedDetected 483 days ago
PythonC++LinuxMachine LearningComputer VisionLLMsRoboticsResearchCollaborationMentoring

About the role

  • We achieve this through partnership, collaboration, and shared commitment.
  • This cross-org collaborative project is synergistic with TRI's robotics divisions' efforts in Diffusion Policy and Large Behavior Models (LBM).
  • An ideal candidate has a strong track record of leading independent research efforts, preferably including mentoring and collaborating with less experienced students and researchers.

Responsibilities

  • Perform closed-loop evaluations in sensor simulations and real-world testing environments to rigorously assess model performance, stability, and scalability.
  • Collaborate with researchers and engineers across TRI, Woven by Toyota, and Toyota's global ecosystem to accelerate model deployment and evaluation in both controlled environments (closed-course) and public road driving.
  • Take the lead on writing and publishing research results in peer-reviewed venues.

Requirements

  • A PhD or equivalent experience in a robotics-relevant or embodied-AI field such as Computer Science, Mathematics, Physics, or Engineering.
  • A consistent track record of publishing at high-impact conferences/journals (CVPR, ICLR, NeurIPS, ICML, CoRL, RSS, ICRA, ICCV, ECCV, PAMI, IJCV, etc.)
  • A consistent track record of independent research.
  • Demonstrated ability to independently formulate and complete a research agenda while collaborating across subject areas.
  • Proficiency in Python and C++ for implementing and evaluating research ideas.
  • Experience training large-scale models, including foundation models (e.g., vision-language models, text-to-video models).
  • Bonus Qualifications
  • Experience with robot motion planning techniques like trajectory optimization, sampling-based planning, and model predictive control, or experience with automated driving domains (e.g., perception, prediction, mapping, localization, planning, simulation).
  • Experience in developing production-level code for real-time operating systems.
  • Experience optimizing runtime-critical systems for Linux, UNIX-like real-time operating systems on automotive-grade compute platforms, and building safety-critical software architectures.

Nice to have

  • Please add a link to Google Scholar and include a full list of publications when submitting your CV for this position.
  • It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment.
  • An employer who violates this law shall be subject to criminal penalties and civil liability.
  • Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.

Compensation

  • The pay range for this position at commencement of employment is expected to be between $200,000 and $287,500/year for California-based roles.

Benefits

  • Research and 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 model architectures using imitation learning and large-scale data, ensuring robust performance across diverse scenarios.
  • Explore multi-modal and language-conditioned models to broaden the applicability of end-to-end policies, using external data sources and transfer learning to enhance generalization.

Company info

  • The Automated Driving Advance Development division at TRI focuses on enabling innovation and transformation at Toyota by building a bridge between TRI research and Toyota products, services, and needs.
  • The Automated Driving Advance Development team is leading a new cross-organizational project between TRI and Woven by Toyota to research and develop a fully end-to-end learned automated driving / ADAS stack.
  • We are looking for a Senior Machine Learning Researcher to join us in developing a state-of-the-art, pixels-to-action, end-to-end system for automated driving.
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