Staff, ML Engineer - E2E
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Die Stelle
Lead the design and deployment of end-to-end (E2E) machine learning models that translate multi-modal sensor inputs into driving decisions.
Architect scalable, differentiable pipelines that integrate perception, behavior prediction, and control for real-world and simulated data.
Define learning objectives aligned with safety, comfort, compliance, and efficiency, and drive large-scale training and evaluation.
Prototype and evaluate approaches such as differentiable planning, imitation learning, reinforcement learning, and world models for autonomous driving behavior.
Collaborate with Perception, Prediction, and Motion Planning teams to align interfaces and ensure coherence between learned and modular components.
Mentor engineers, contribute to robust evaluation frameworks (closed-loop simulation and on-road validation), and stay at the forefront of ML research.
Architect scalable, differentiable pipelines that integrate perception, behavior prediction, and control for real-world and simulated data.
Define learning objectives aligned with safety, comfort, compliance, and efficiency, and drive large-scale training and evaluation.
Prototype and evaluate approaches such as differentiable planning, imitation learning, reinforcement learning, and world models for autonomous driving behavior.
Collaborate with Perception, Prediction, and Motion Planning teams to align interfaces and ensure coherence between learned and modular components.
Mentor engineers, contribute to robust evaluation frameworks (closed-loop simulation and on-road validation), and stay at the forefront of ML research.
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