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

What you'll do

• Design and train generative, imitation, and reinforcement-learning models to improve driving-system planning and reasoning.
• Build, pre-train, and fine-tune LLM/VLM/VLA systems and develop strategies for generating and collecting training data.
• Deploy models with cross-functional teams and integrate them with vehicle firmware to meet safety, reliability, and performance standards.

What they ask for

• Hands-on experience building LLMs, VLMs, or VLAs from scratch, or a proven track record as a top-tier coder passionate about autonomous systems.
• Deep understanding of modern deep learning architectures and optimization techniques; experience deploying production-grade ML models at scale for self-driving, robotics, or related fields.
• Strong Python programming skills and proficiency with major deep learning frameworks; familiarity with C++ for safety-critical deployment and integration.
• PhD with 4+ years, or MS (or equivalent experience) with 6+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.

Nice to have

• Experience with LLM/VLM/VLA systems deployable to autonomous vehicles or general robotics; publications, open-source contributions, or competition wins in these areas.
• Expertise in real-world AV behavior and motion planning, large-scale datasets and models, or real-time optimization for resource-constrained environments.

Pay

184,000 USD - 287,500 USD (base salary, Level 4); 224,000 USD - 356,500 USD (base salary, Level 5)

Tools

LLMs, VLMs, VLAs, Python, C++

AI focus

Build and deploy large-scale generative, imitation, and reinforcement-learning models, including LLM/VLM/VLA systems, for autonomous driving and robotics; improve planning, reasoning, and training-data quality.