We are in need of skilled engineers to join our autonomous driving team to invent, execute, and deploy pioneering end-to-end autonomous driving systems. Our strategy has progressed from AI 1.0 constructing a driver from the ground up to AI 2.0 training an intelligent agent to drive. This is achieved by developing LLMs, VLMs, and VLAs to offer exceptional reasoning, planning capabilities, and interaction with the driving system for autonomous driving and general robotics. Lets innovate the future of autonomytogether!
What you will be doing:
Build and train innovative large-scale modelsincluding generative, imitation, and reinforcement learningto improve the planning and reasoning capabilities of our driving systems.
Explore novel data generation and collection strategies to improve diversity and quality of training datasets. Develop, pre-train, and optimize LLM/VLM/VLA models for autonomous driving and robotics applications.
Collaborate cross-functionally to deploy and integrate AI models into vehicle firmware.
Deliver production-quality, safety-critical software that meets performance, safety, and reliability standards.
What we need to see:
PhD or Master's degree with equivalent experience.
8+ years of experience.
Hands-on experience training LLMs/VLMs/VLAs from scratch, or a proven record as a top-tier ML engineer/researcher passionate about autonomous systems.
Strong programming skills in Python and proficiency with major deep learning frameworks. Basic familiarity with C++ for model deployment and integration in safety-critical systems.
Comprehensive grasp of current deep learning structures and improvement methods. Consistent track record of deploying production-grade ML models for self-driving, robotics, or related fields at scale.
Ways to stand out from the crowd:
Experience developing and shipping LLM/VLM/VLA solutions for autonomous vehicles or general robotics products.
Publications, contributions to open-source projects, or victories in competitions connected to LLM/VLM/VLA systems.
Profound comprehension of behavior and motion planning in real-world autonomous vehicle (AV) applications.
Experience building and training large-scale datasets and models and/or training agents with reinforcement learning.
