Applied Intuition is looking for a lead software engineer to accelerate the adoption of safe, AI-driven machines by leading the engineering team in prototyping, evaluating, refining, and deploying state-of-the-art ML capabilities for their autonomous vehicle stack.
Requirements
- 5+ years of industry experience in autonomous driving expertise in developing and deploying machine learning models for prediction and planning in autonomous vehicle systems
- Background architecting integrated ML systems that connect perception, prediction, and planning modules
- Proficiency in C++ and Python for large-scale ML system development
- Experience mentoring and leading teams of ML engineers in large-scale, cross-functional projects
- Experience with imitation learning, reinforcement learning, and scalable training pipelines for autonomous driving
- Familiarity with generative AI, deep neural networks, and state-of-the-art ML frameworks (e.g., TensorFlow, PyTorch)
- Prior work on joint prediction and planning models for Level 4 or higher autonomous vehicles
Responsibilities
- Lead the development of machine learning models for joint behavior prediction and planning, with the goal of end-to-end differentiable autonomy
- Architect integrated ML systems that reason over latent scene representations from perception to directly inform or generate trajectory decisions
- Implement data-driven approaches that optimize the full autonomy stack jointly
- Collaborate tightly with Perception, Mapping, and Simulation teams to design shared representations and scalable training loops, including imitation and reinforcement learning
- Mentor a team of ML engineers focused on reasoning, joint prediction and planning, and generalization across ODDs, aligned with the trucking roadmap
Other
- We are an in-office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week.
- Mentor a team of ML engineers
