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

This is a fully remote position, open to applicants in California.

📋 Description

• Create and develop cutting-edge large-scale models, including generative, imitation, and reinforcement learning, aimed at enhancing planning and reasoning capabilities.

• Construct, pre-train, and fine-tune LLM/VLM/VLA systems for practical applications in autonomous driving and robotics.

• Investigate innovative data generation and collection methods to diversify and enhance the quality of training datasets.

• Collaborate with interdisciplinary teams to implement AI models in production while ensuring they meet performance, safety, and reliability standards.

• Seamlessly integrate machine learning models with vehicle firmware to produce high-quality, safety-critical software.

⛳️ Requirements

• Practical experience in developing LLMs, VLMs, or VLAs from the ground up, or a distinguished background as an exceptional coder with a passion for autonomous systems.

• In-depth knowledge of contemporary deep learning architectures and optimization methods.

• Demonstrated experience in deploying production-grade ML models for self-driving, robotics, or related industries on a large scale.

• Proficient programming skills in Python along with expertise in major deep learning frameworks.

• Understanding of C++ for model deployment and integration within safety-critical systems.

• PhD with over 4 years of relevant experience in Computer Science, Computer Engineering, or a similar technical domain, or a Master’s degree (or equivalent experience) with more than 6 years of relevant experience.

• Experience with LLM/VLM/VLA systems that can be applied to autonomous vehicles or general robotics.

• Contributions through publications, open-source projects, or victories in competitions related to LLM/VLM/VLA systems.

• Profound understanding of behavior and motion planning in real-world autonomous vehicle applications.

• Experience in constructing and training large-scale datasets and models.

• Proven capability to optimize algorithms for real-time performance in resource-limited environments.

• Strong history of managing projects from initial concept through to production deployment.

🏝️ Benefits

• Equity

• Benefits