Senior AI/ML Engineer

Job Description

Senior AI/ML Engineer, AV ML Infra 

We’re General Motors (GM), a company driving the future of mobility with advanced self-driving and electric vehicle technologies. 

We’re building the world’s most innovative autonomous vehicles to safely connect people to the places, things, and experiences they care about. We believe self-driving vehicles will help save lives, reshape cities, give back time in transit, and restore freedom of movement for many. 

GM employees have the opportunity to grow and develop while learning from leaders at the forefront of their fields. With a culture of internal mobility, there’s an opportunity to thrive in a variety of disciplines. This is a place for dreamers and doers to succeed. 

If you are looking to play a part in making a positive impact in the world by advancing the revolutionary work of self-driving vehicles, join us. 

About the team: 

The AV ML Infra team at GM builds ML infrastructure designed to meet the unique demands of AI and ML innovation, supporting a wide range of use cases across teams such as Embodied AI, Simulation, Data Science, and more. We enable scalable and efficient ML experimentation, enhance the productivity of ML engineers, and drive the adoption of cutting-edge ML techniques. 

Our ML infrastructure includes: 

• AI Validation & Inference: Ensures robust model performance by running large-scale simulation workloads and managing reliable ML inference pipelines. 
   

• ML Compute: Streamlines and optimizes large-scale ML training and inference across cloud and on-prem compute resources. 
   

• AV Pipelines & Lineage: Automates ML workflows while tracking data and model lineage across diverse infrastructures, accelerating engineering velocity and ensuring reproducibility. 

Together, these tools and systems empower GM to tackle the complexities of autonomous driving technology and expedite our path to commercialization. 

Position Overview: 

As a Senior AI/ML Engineer, you will focus on designing and implementing scalable ML infrastructure solutions. You will take ownership of key technical projects, provide mentorship to junior engineers, and collaborate across teams to solve complex problems. This is an individual contributor role emphasizing deep technical impact rather than leadership of large teams. 

Note: This role is part of an ML infrastructure engineering team and does not involve applying machine learning models for specific tasks. The focus is on developing infrastructure products that empower GM teams to perform machine learning and data science at scale. 

What you’ll be doing: 

• Design & Implementation: Utilize the latest cloud technologies (GCP/Azure) to design, implement, and test scalable distributed computing and data processing solutions in the cloud. 

• Project Ownership: Take ownership of technical projects from inception to completion, contribute to the product roadmap, and make informed decisions on major technical trade-offs. 

• Collaboration: Engage effectively in team planning, code reviews, and design discussions, considering the impact of projects across multiple teams while proactively managing conflicts. 

• Mentor