Principal ML Engineer - Embodied AI Scaling Foundations
Description
At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We're turning today's impossible into tomorrow's standard -from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features.
Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale.
The Data Scaling team owns the Data Flywheel for AV Foundation model development and successive fine tuning. It defines the composition of the data that is needed for the AV to learn behaviors at scale and deliver the driving behaviors necessary for the product success. The team owns the definition and processes for data quality across the data loop.
The team directly works on and delivers ML models to the product that successively go up the Data Scaling curves, thereby directly impacting AV product performance through smart use of data. As part of this work, the team builds scalable systems and pipelines that attempt to 10x the data used, its diversity and impact on the models with successive major releases. The team uses existing very large datasets that GM has access to internally as well as defines the next generation of highest value datasets that GM continues to collect - both from real driving by GM and retail fleets, but also synthetic sim-based datasets.
Why Join Us?
- Scale up AV foundation model pre-training and fine-tuning with data to its maximum capacity - into billions+ of examples - across different sources, delivering the maximum value to the model through every additional example.
- Work with cutting-edge technology and a collaborative, high-impact team of AI/ML engineers, data scientists and engineers who are passionate about leveraging advanced AI techniques to drive innovation for L2, L3 and L4 applications.
- Contribute to the safety, reliability, and scalability of next-generation autonomous vehicles.
As a Principal Technical Lead in the Embodied AI Data Foundations organization, you will be a senior individual contributor driving cutting-edge end-to-end machine learning solutions maximally leveraging multiple sources of data including real and synthetic datasets, directly impacting autonomous driving performance. Towards this goal, you will lead the development of novel curation algorithms, pre-training, post-training and fine-tuning recipes for training AV models.
Your role is pivotal in designing, architecting, and deploying data curation and training pipelines while simultaneously delivering advanced ML models that continue to go up scaling curves. These models will reliably and safely navigate diverse real-world scenarios and conditions. You'll lead critical technical initiatives, collaborate closely with cross-functional teams, mentor ML engineers, and significantly shape the future of onboard and offboard ML capabilities.
What You'll Do:
- Design and implement technologies that align our models to GM's mission.
- Apply techniques such as unsupervised pre-training, imitation learning, reinforcement learning, guidance, and selection to raise the performance of our models and provide a layer safety and reliability.
- Collaborate with cross-functional teams to integrate & align distillation recipes of foundation models for onboard driving models.
- 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 and alignment methods to translate research into real-world impact.
- Proven experience delivering applied research in the wild and maintaining best practices while working on tight deadlines.
- Proficiency in frameworks such as PyTorch and languages such as Python.
- 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.
Remote/Hybrid: This role is categorized as fully remote or hybrid.
Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.
Company Vehicle : Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.
Relocation: This job may be eligible for relocation benefits.
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About GM
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