Senior Staff Machine Learning Engineer – Autonomous Driving Foundation Models
XPENGSanta Clara, California, United States · Posted 5 months agoDescription
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Architectural Leadership: Lead the design of end-to-end VLA architectures, bridging multi-modal perception with high-level linguistic reasoning and precise action generation.
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World Model Development: Drive R&D in generative world models (latent dynamics) to create high-fidelity, controllable driving simulations for closed-loop training and evaluation.
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Policy Evolution: Apply Advanced RL (Online/Offline) and IL to refine driving policies, focusing on long-horizon planning and complex multi-agent interactions.
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Scaling & Data Strategy: Define scaling laws for driving foundation models, overseeing data curation, automated labeling, and post-training at a multi-billion parameter scale.
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Global Generalization: Lead the model’s adaptation strategy for overseas road conditions, ensuring robust performance across varying traffic laws and driving cultures.
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5-8 years of expertise in Deep Learning, with a significant track record in VLM, VLA, or Embodied AI.
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Proven experience in training and deploying Foundation Models (Transformers, LLMs) at scale.
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Deep understanding of Sequential Decision Making, World Models, or Policy Gradient methods.
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Mastery of PyTorch and expertise in distributed training (DeepSpeed, Megatron, etc.).
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A "Product-First" mindset: The ability to balance cutting-edge research with the deterministic requirements of L4 production vehicles.
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A fun, supportive and engaging environment
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Infrastructures and computational resources to support your ML model development/research.
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Opportunity to work on cutting edge technologies with the top talent in the field.
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Opportunity to make significant impact on transportation revolution by the means of advancing autonomous driving
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Competitive compensation package
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Snacks, lunches, dinners, and fun activities
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