Motional is looking for a Machine Learning Integration Engineer to deploy, optimize, and maintain ML-driven planning and control algorithms for real-time autonomous driving. You will bridge advanced machine learning with safety-critical, resource-constrained vehicle platforms, working within a mission-driven company building safe and transformative mobility solutions.
What You'll Do
- Deploy ML-based motion planning and control models onto vehicle platforms, ensuring performance under resource constraints.
- Optimize models for inference speed, latency, and memory footprint without sacrificing accuracy or safety.
- Collaborate with motion planning, controls, and perception teams to integrate ML components into the end-to-end autonomous driving stack.
- Build scalable deployment infrastructure including evaluation pipelines, model packaging, benchmarking, and automated validation.
- Validate model performance in both simulation and on-road testing, analyzing results and driving iterative improvements.
- Maintain production-quality code in C++ and Python.
What We're Looking For
- BS/MS/PhD in Robotics, Computer Science, Electrical Engineering, or a related field.
- Experience deploying ML systems in real-world robotics, embedded, or autonomous platforms.
- Experience with reinforcement learning.
- Strong software engineering skills in C++ and Python, with knowledge of modern development practices.
- Hands-on experience with ML frameworks (PyTorch, TensorFlow) and model optimization for deployment.
- Familiarity with GPU acceleration, or inference optimization (e.g., TensorRT, CUDA).
- Strong problem-solving skills and ability to debug complex systems under production constraints.
Nice to Have
- Experience with autonomous vehicle motion planning, control algorithms (MPC, LQR, PID), or reinforcement learning–based methods.
- Publications in relevant ML or robotics conferences (ICRA, NeurIPS, CoRL, RSS, etc.).
- Experience with ROS, AUTOSAR, or other real-time robotics frameworks.
- Knowledge of numerical optimization and its applications in trajectory generation.
Technical Stack
- C++, Python
- PyTorch, TensorFlow
- CUDA, TensorRT
Team & Environment
You will collaborate across motion planning, controls, and software engineering teams within a highly collaborative environment of ML researchers, software engineers, and controls experts.
Benefits & Compensation
- Compensation: $142,000—$225,000 USD + company equity.
- Medical, dental, vision insurance.
- 401k with company match.
- Health saving accounts.
- Life insurance.
- Pet insurance.
Motional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees.
