Staff ML Engineer - End-to-End (E2E)
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El puesto
Lead end-to-end model design and development mapping multi-modal sensor inputs (camera, LiDAR, radar, HD maps) to driving actions or costs.
Drive large-scale training and evaluation for E2E learning, integrating data from perception, behavior prediction, and control systems.
Develop learning objectives that align with real-world driving metrics: safety, comfort, compliance, and efficiency.
Architect scalable pipelines for multi-task, multi-modal learning using real-world and synthetic data.
Prototype and evaluate new paradigms such as differentiable planning, imitation learning, reinforcement learning, and world models for AV behavior.
Mentor engineers and scientists in large-scale experimentation and data-driven debugging, collaborating across perception, prediction, and motion planning teams.
Drive large-scale training and evaluation for E2E learning, integrating data from perception, behavior prediction, and control systems.
Develop learning objectives that align with real-world driving metrics: safety, comfort, compliance, and efficiency.
Architect scalable pipelines for multi-task, multi-modal learning using real-world and synthetic data.
Prototype and evaluate new paradigms such as differentiable planning, imitation learning, reinforcement learning, and world models for AV behavior.
Mentor engineers and scientists in large-scale experimentation and data-driven debugging, collaborating across perception, prediction, and motion planning teams.
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