Research Scientist, Simulation Agents

Waabi
Remote US & CanadaPosted 25 March 2026

Job Description

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech. With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai The Behaviors team at Waabi develops cutting-edge simulation agents and scenario generation algorithms for Waabi World, our simulation platform. As a Research Scientist on the Behaviors team, you will work closely with our multidisciplinary team of research scientists and engineers to invent the next generation of models and algorithms that power Waabi World. Your work will define the scenarios that push our self-driving system to its limits, generate the training signal that makes them better, and form a core pillar of our scientific safety case to put them on the road. You will... Own and pursue a research agenda to develop realistic and controllable simulation agents. Advance the state-of-the-art in imitation learning, reinforcement learning, generative models, foundation models, planning and search, and other related areas for simulation agents. Collaborate with our simulation, autonomy, and safety teams to define high-impact research problems, ship solutions into production, and drive progress towards Waabi’s milestones. Mentor junior scientists and interns; foster a culture of scientific rigor and rapid experimentation. Publish high-impact research at top-tier conferences in machine learning or robotics. Qualifications: Masters/PhD in machine learning, computer science, engineering, or a related field. Strong background in imitation learning and/or reinforcement learning. Publications in top-tier conferences or journals related to machine learning or robotics. Proficiency with modern ML frameworks such as PyTorch, TensorFlow, or Jax. Bonus: Experience in self-driving, traffic simulation, or a related field. Proven ability to take research from prototype to production systems. Strong software engineering skills, including experience with large-scale training or simulation.
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