- Company Name
- General Motors
- Job Title
- Staff AI ML Engineer
- Job Description
-
Job Title: Staff AI ML Engineer
Role Summary:
Lead the design, development, and operation of end‑to‑end AI and machine‑learning platform components, delivering high‑availability services that enable ML engineers to build, test, deploy, and monitor models within a vehicle AI ecosystem.
Expectations:
* Own the full lifecycle of AI platform features from concept to production, ensuring reliability, scalability, and compliance.
* Drive cross‑functional collaboration with ML, research, and software teams, translating broad technical challenges into actionable initiatives.
* Mentor and elevate engineering talent while influencing architectural standards across the organization.
Key Responsibilities:
* Build and maintain UX experiences and agentic workflows that streamline ML engineer productivity.
* Develop backend integrations and unified data pipelines for data collection, model training, evaluation, and deployment.
* Enhance system observability, debuggability, and operational excellence, establishing metrics for platform health and performance.
* Define and enforce enterprise, systems, and integration architecture, ensuring security and compliance.
* Create and manage CI/CD pipelines, configuration management, and artifact repositories in cloud environments.
* Lead design reviews, approve technical documentation, and improve engineering processes.
* Identify opportunities for innovation, experimentation, and process improvement.
Required Skills:
* Proven experience building, deploying, and operating high‑availability services at scale.
* Leadership on large technical initiatives from ideation through operationalization.
* Architecture expertise: enterprise, systems, integration, and workflow frameworks.
* Strong programming proficiency in Python, Java, or Go; front‑end skills in React, Angular, or equivalent (JavaScript/TypeScript).
* Cloud infrastructure, automation, CI/CD, and configuration management experience.
* Familiarity with Web services, JSON, GraphQL, agentic workflows, and data visualization.
* Knowledge of ML pipelines, experimental design, and model deployment concepts.
Required Education & Certifications:
* BS, MS, or PhD in Computer Science, Mathematics, Physics, or a related technical field.