Principal ML Engineer - Embodied AI

Description
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 technologies that will deliver scaling laws for our Foundation Models for various applications.

• Scale up foundation model pre-training with data to its maximum capacity - into billions+ of examples - across different sources, delivering the maximum value to the model through every additional example.

• Directly work on or collaborate closely with teams that scale up training and eval infrastructure to handle multi-billion examples across distributed machines and GPUs, while providing efficient time to model checkpoint.

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

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

• Proven experience in solving data scaling challenges, ranging from data diversity, data quality and building best practices to incorporate multiple data sources in large models.

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

• Proven experience in building and scaling large model training pipelines that are performant and enable quick iteration by distributed teams.

• 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.

Compensation : The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.

• The salary range for this role is $259,000 to $396,300. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.

• Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.

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.
Relocation: This job may be eligible for relocation benefits.
About GM
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