Research Scientist, Learnable Planner

Position Overview

• Location Type: Hybrid (Toronto, San Francisco, Dallas)
• Job Type: Full-time
• Salary: Not specified

Waabi, founded by AI pioneer Raquel Urtasun, is an AI company developing next-generation self-driving technology. They are building the next generation of self-driving technology with a world-class team and an innovative approach to “drive” safely in the real world, bringing the promise of self-driving closer to commercialization. Waabi is backed by leading investors. With offices in Toronto, San Francisco, and Dallas, Waabi is growing quickly and seeking diverse, innovative, and collaborative candidates. To learn more, visit: www.waabi.ai

Team: Motion Planning

The Motion Planning team delivers the core module within the autonomy stack that makes decisions and generates trajectories for our self-driving trucks.

Responsibilities

• Design and execute on a research agenda for deep-learning based motion planning for self-driving.
• Leverage and advance the state-of-the-art in robotics and machine learning to enable safe self-driving at scale, utilizing techniques in:
  • Imitation and reinforcement learning
  • Planning and search
  • Perception and prediction
  • Simulation
  • Foundation models
• Support deploying solutions to production systems, collaborating closely with platform teams to ensure seamless integration of research findings.
• Stay up-to-date and advance beyond the state-of-the-art in artificial intelligence, machine learning, computer vision, and self-driving technologies.
• Champion engineering excellence, ensuring high-quality, well-structured, and tested code.
• Submit and publish work externally at top machine learning, computer vision, and robotics conferences (NeurIPS, ICLR, ICML, CVPR, etc.) and on the company blog.

Requirements

• Education: MS/PhD degree in Computer Science, AI, Machine Learning, Computer Vision, Robotics, or a related field. Exceptional Bachelor’s students will also be considered.
• Experience: Demonstrated research experience through previous internships, work experience, research projects, and publications at top conferences.
• Technical Skills:
  • Experience in planning/decision-making approaches (e.g., imitation learning, reinforcement learning, optimal control, optimization-based approaches, search methods, probabilistic decision making).
  • Strong quantitative background and coursework in linear algebra, calculus, and probability.
  • Proficient in reading and coding in Python.
• Passion: Passionate about self-driving technologies, solving hard problems.

Application Instructions

• Not specified in the provided text. (Please refer to the Waabi website for application details).