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. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.