Staff AI/ML Full-Stack Engineer: End-to-End AI Platforms

About the team The AV ML Infra team builds end‑to‑end ML platforms and developer‑facing products to support AI and ML innovation across teams such as Embodied AI, Simulation, and Data Science. ML infrastructure includes: AI Validation & Inference: Ensures robust model performance by running large‑scale simulation workloads and managing ML inference pipelines. ML Compute: Streamlines 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. Position Overview As a Staff AI/ML Full‑Stack Engineer, you will design and build end‑to‑end software products, owning user‑facing interfaces, backend services, and cloud infrastructure. The role is hands‑on, focused on technical depth, system design, and product impact. What you’ll be doing Full‑Stack Development: Design, implement, and maintain user‑facing web applications and internal tools; build scalable backend services and APIs. Frontend Engineering: Build modern responsive UIs using React, Angular, or similar, and collaborate with UX partners to deliver intuitive workflows. Design & Implementation: Use GCP/Azure to design, implement, and test scalable distributed computing solutions. Project Ownership: Lead projects from inception to completion, contribute to product roadmap, and make technical trade‑off decisions. Collaboration: Engage in planning, code reviews, design discussions; manage conflicts across teams. Mentorship & Recruitment: Conduct technical interviews, onboard, and mentor engineers and interns. What you must have 5+ years professional software engineering, including full‑stack development. Experience building production‑grade web applications. 3+ years leading large‑scale initiatives. Proficiency building scalable cloud infrastructure using Python, C++, Golang, or similar. Experience working with relational and NoSQL databases. Demonstrated ability to develop and maintain systems at scale. A Bachelor’s, Master’s, or Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, or equivalent. Passion for autonomous vehicle technology. Strong attention to detail and commitment to accuracy. Track record of efficiently solving complex problems. Willingness to embrace uncertainty and wear multiple hats. Bonus Points Experience with Google Cloud, Microsoft Azure, or AWS. Experience with Kubeflow, Flyte, Airflow, etc. Experience with Kubernetes. Understanding of ML models and pipelines. Proficiency in Python/C++/Golang. Relevant publications. Compensation The expected base compensation is $218,800 – $335,300. Bonus potential depends on company performance, job level, and individual performance. Benefits Health, dental, vision, HSA, FSA, retirement, sickness & accident, life insurance, paid vacation & holidays, tuition assistance, employee assistance program, GM vehicle discounts. Non‑Discrimination and Equal Employment Opportunities (U.S.) General Motors is committed to a workplace free of unlawful discrimination and fosters inclusion and belonging. Employment decisions are made on a non‑discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy, sexual orientation, gender identity, veteran status, or any other protected status. Accommodations General Motors offers reasonable accommodations to job seekers with disabilities. Candidates may email or call to request accommodations. #J-18808-Ljbffr Israelvcforum