Staff ML Engineer - Offboard Embodied AI

Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to the Mountain View Technical Center in the Bay Area three times per week, at minimum. 

Role: In this role, you will be at the forefront of developing and deploying large-scale Foundation Models (FMs) that enhance our automotive technologies at General Motors focused on Autonomous Driving & Robotics. You will work closely with a dynamic team of AI and ML researchers, data scientists and engineers who are passionate about leveraging advanced AI techniques to drive innovation for L2, L3 and L4 applications. Your contributions will directly impact our ability to deliver cutting-edge solutions that meet the needs of our customers.  

What You'll Do:  

• Design and implement large-scale Foundation Models for various applications, leveraging recent advancements in AI and robotics. 

• Collaborate with cross-functional teams to integrate & built distillation recipes of Robotics foundation models for onboard driving models. 

• Analyze and optimize model performance, ensuring efficient training and deployment. 

• Conduct research and stay updated on the latest advancements in AI frameworks and libraries. 

• Lead projects from ideation to deployment, documenting learnings and best practices along the way. 

• Mentor junior team members and contribute to a culture of knowledge sharing and continuous improvement. 

Your Skills & Abilities:  

• Bachelor’s, Master’s or PhD degree in Computer Science with a focus in Robotics and or Machine Learning, or a related field. 

• Proven experience working with large-scale Foundation Models, including LLMs, VLAs and vision-focused models. 

• Proficiency in frameworks such as PyTorch and TensorFlow, with experience in libraries like HuggingFace and OpenAI GPT. 

• Strong data processing skills using tools like Numpy, Pandas, and Apache Spark. 

• Excellent communication skills to effectively collaborate with diverse teams and stakeholders. 

• Experience deploying foundation models into production environments and understanding the end-to-end process. 

• Previous experience in Robotics or Autonomous Driving.