Staff ML Engineer - Embodied AI Onboard Autonomy

Job description

Job responsibilities

• Drive the design, development, and deployment of advanced onboard ML models, delivering end-to-end solutions capable of real-time inference and robust autonomous driving performance.
• Lead and architect complex machine learning projects, from conception through validation to onboard implementation, emphasizing scalability, robustness, and safety-critical operation.
• Champion innovation in neural network architectures, training methodologies, and inference optimization strategies suited for real-time onboard deployment.
• Provide technical mentorship and thought leadership, elevating engineering practices, and fostering ML innovation across teams.
• Collaborate closely with multidisciplinary engineering groups, ensuring seamless integration of ML capabilities into autonomous vehicle systems.
• Influence technical roadmaps, shaping strategic ML priorities aligned with company objectives and product milestones.

Job requirements

• Master's or Ph.D. in Machine Learning, Robotics, Computer Science, Electrical Engineering, or a related technical field.
• 4+ years of experience working with large-scale Foundation Models, including LLMs, VLAs and vision-focused models.
• Extensive experience developing and deploying advanced ML systems, particularly in end-to-end real-time onboard applications.
• Proven track record as a technical expert in developing robust deep learning models that directly map sensor data to actionable outputs within safety-critical systems.
• Deep expertise in state-of-the-art computer vision techniques, neural architectures, representation learning, real-time inference, model optimization, and robustness under uncertainty.
• Strong software engineering proficiency, particularly Python and C++, alongside extensive hands-on experience with modern ML frameworks (PyTorch, TensorFlow, JAX).
• Excellent communication, collaboration, and mentoring abilities, comfortable influencing technical strategy and guiding ML engineering excellence across the organization.
• AV/ADAS experience is a big plus