Staff Machine Learning Engineer, Vehicle Behaviors

Stack AV is developing revolutionary AI and advanced autonomous systems aimed at enhancing safety, reliability, and efficiency in the trucking transportation industry. The Staff Machine Learning Engineer will be responsible for developing and deploying motion planning components for next-generation self-driving systems, focusing on real-time, safety-critical applications.

Responsibilities:

• Design, scope, implement, and integrate machine learning systems to solve on-vehicle behavior problems in a real-time, resource-constrained environment
• Develop tooling and infrastructure necessary to measure and iterate on ML models
• Provide input in the technical direction for the team, and work cross-functionally to develop safe systems. This will include working closely with other teams such as perception, localization, and controls to ensure that the input to the motion planning modules is appropriate
• Work closely with systems engineers to ensure a safe, well tested product is delivered
• Work closely with verification teams to ensure proper testing and validation of the motion planning modules. Make extensive use of unit testing, simulation, and log simulation to properly validate their work
• Collaborate with other autonomy teams including perception, localization, controls, etc. to ensure solutions are appropriate for real-world performance
• Provide input to team roadmaps and ensure product features are properly prioritized
• Identify bottlenecks and limitations in system performance, and develop novel motion planning components to unlock new capabilities and ensure a reliable system
• Be involved in experimentation, design and iteration exercises, and help to align stakeholders by using strong presentation and communication skills

Requirements:

• Strong Python skills
• Experience with key ML libraries like PyTorch and TensorRT
• Experience with cloud orchestration tools like Flyte
• Exceptional written and verbal communications skills
• Experience developing code for real-world robotics/semi-autonomous platform