Role overview
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What you'll work on
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.
What we're looking for
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 .
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.
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.
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About GM
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