over 1 year ago
Remote, United States +5 moreMid Level
Base Salary
$159k - $296k/yr
Responsibilities
- Integrate machine learning models into the production motion-planning stack from development through validation, deployment, and monitoring.
- Develop simulation interfaces and pipelines for testing prototype and production planning models.
- Collaborate with motion-planning sub-teams and research scientists to improve planner architecture and develop representations for end-to-end solutions.
- Write high-quality, well-structured, and tested code while supporting engineering excellence.
- Work with large datasets and Waabi World, the company’s high-fidelity closed-loop simulator.
- Apply advances from artificial intelligence, machine learning, computer vision, and self-driving research.
- Contribute to publishing research findings in conferences and on Waabi’s blog.
Requirements
- Master’s or PhD in machine learning, computer science, engineering, or a related field; exceptional bachelor’s students may also be considered.
- Experience with ML-based or classical planning and decision-making techniques, including imitation learning, reinforcement learning, optimization-based approaches, search methods, or probabilistic reasoning.
- Ability and interest in turning research ideas into practical real-world solutions.
- Solid understanding of computing fundamentals, including code efficiency.
- Experience with deep learning frameworks such as PyTorch.
- Proficiency in Python, Rust, C++, and/or CUDA.
- Preferred experience deploying ML/DL models to production motion-planning or related robotics stacks.
- Preferred experience with model evaluation, introspection, and fine-tuning.
- Strong understanding of machine learning literature and current state-of-the-art techniques is preferred.
- Familiarity with model compilation, TensorRT, and CUDA kernels is preferred.
Benefits
- Competitive compensation and equity awards.
- Medical, dental, and vision coverage for full-time employees.
- Unlimited vacation.
- Flexible hours and work-from-home support.
- Daily drinks, snacks, and catered meals when working in the office.
- Regular on-site, off-site, and virtual team-building activities and social events.
- US-based role with offices in Toronto, San Francisco, Dallas, and Pittsburgh; workplace support includes flexible hours and work-from-home options.
Categories
ML EngineeringRobotics
