5+ years professional software engineering experience
Production-grade web application development
Scalable cloud infrastructure on gcp or azure
General Motors (GM) is seeking a Staff AI/ML Full-Stack Engineer for its AV ML Infra team, focusing on developing end-to-end software products that support AI and ML innovations in the autonomous vehicle sector. The role combines technical depth with project ownership and mentorship, requiring substantial experience in software engineering and cloud infrastructure.
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Job Summary
This role involves designing and building end-to-end software products that empower GM teams to perform machine learning at scale without applying models directly.
The team focuses on enabling scalable ML experimentation, optimizing compute resources, and automating workflows for autonomous driving technologies.
Employees are eligible for a company vehicle evaluation program where they can drive and evaluate General Motors vehicles upon completing a motor vehicle report review.
Matching Summary
Match Score: 85
General Motors (GM) is seeking a Staff AI/ML Full-Stack Engineer for its AV ML Infra team, focusing on developing end-to-end software products that support AI and ML innovations in the autonomous vehicle sector. The role combines technical depth with project ownership and mentorship, requiring substantial experience in software engineering and cloud infrastructure.
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Salary
Base: $218,800- $335,300; Bonus: Incentive pay based on company and individual performance; Benefits: Medical, dental, vision, retirement savings, tuition assistance, and vehicle discounts
Skills & Requirements
Must-have
5+ years professional software engineering experience
Production-grade web application development
Scalable cloud infrastructure on GCP or Azure
Proficiency in Python, C++, or Golang
Relational and NoSQL database management
Nice-to-have
Experience with Kubeflow, Flyte, or Airflow
Kubernetes orchestration platform knowledge
Understanding of ML models and pipelines
Relevant academic publications
Startup mentality embracing uncertainty
Key Requirements
Bachelor's, Master's, or Ph.D. in Computer Science or related field