Senior Staff Machine Learning Engineer – Autonomous Driving Foundation Models

Key Responsibilities

• Architect the transition from behavior cloning to intelligent, zero-shot decision-making in diverse global markets.
• Lead the design of end-to-end VLA architectures, bridging multi-modal perception with high-level linguistic reasoning and precise action generation.
• Drive R&D in generative world models (latent dynamics) to create high-fidelity, controllable driving simulations for closed-loop training and evaluation.
• Apply Advanced RL (Online/Offline) and IL to refine driving policies, focusing on long-horizon planning and complex multi-agent interactions.
• Define scaling laws for driving foundation models, overseeing data curation, automated labeling, and post-training at a multi-billion parameter scale.
• Lead the model’s adaptation strategy for overseas road conditions, ensuring robust performance across varying traffic laws and driving cultures.

Qualifications

• 5-8 years of expertise in Deep Learning, with a significant track record in VLM, VLA, or Embodied AI.
• Proven experience in training and deploying Foundation Models (Transformers, LLMs) at scale.
• Deep understanding of Sequential Decision Making, World Models, or Policy Gradient methods.
• Mastery of PyTorch and expertise in distributed training (DeepSpeed, Megatron, etc.).
• A "Product-First" mindset: The ability to balance cutting-edge research with the deterministic requirements of L4 production vehicles.

Pay

The base salary range for this full-time position is $244,140-$413,160, in addition to bonus, equity and benefits.