Deep Learning Senior Engineer, End-To-End Autonomous Driving

What you'll do

• Design and train large-scale generative, imitation, and reinforcement learning models for driving systems.
• Build, pre-train, and fine-tune LLM, VLM, and VLA systems for autonomous driving and robotics.
• Develop novel data generation and collection strategies to improve training dataset diversity and quality.
• Integrate machine learning models directly with vehicle firmware for safety-critical software production.
• Deploy AI models in production environments while ensuring performance, safety, and reliability standards.
• Optimize algorithms for real-time performance in resource-constrained environments.

What we're looking for

• Hands-on experience building LLMs, VLMs, or VLAs from scratch or a proven track record as a top-tier coder.
• Deep understanding of modern deep learning architectures and optimization techniques.
• Proven record of deploying production-grade ML models for self-driving, robotics, or related fields at scale.
• Strong programming skills in Python and proficiency with major deep learning frameworks.
• Familiarity with C++ for model deployment and integration in safety-critical systems.
• PhD with 4+ years or MS with 6+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.
• Experience with LLM/VLM/VLA systems deployable to autonomous vehicles or general robotics (preferred).
• Publications, open-source contributions, or competition wins related to LLM/VLM/VLA systems (preferred).