Staff Automation Ai Engineer - Manufacturing Engineering

General Motors

Hybrid
Domain-specific lora fine-tuning
Multi-modal ai models
Production-grade ml infrastructure
The Role: General Motors is seeking an experienced Automation AI Staff Engineer with deep expertise in manufacturing systems and production AI to drive the next generation of intelligent manufacturing solutions

Job Summary

  • The Role: General Motors is seeking an experienced Automation AI Staff Engineer with deep expertise in manufacturing systems and production AI to drive the next generation of intelligent manufacturing solutions.
  • You will work at the intersection of cutting-edge AI technology and real-world manufacturing operations, collaborating with plant engineers, quality teams, robotics specialists, and IT infrastructure teams to digitize Manufacturing.
  • This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week.

Matching Summary

The Role: General Motors is seeking an experienced Automation AI Staff Engineer with deep expertise in manufacturing systems and production AI to drive the next generation of intelligent manufacturing solutions.

Skills & Requirements

Must-have

  • Domain-Specific LoRA fine-tuning
  • multi-modal AI models
  • production-grade ML infrastructure
  • Kubernetes deployments
  • machine vision systems
  • MLOps best practices

Nice-to-have

  • custom training loops
  • advanced model compression
  • self-supervised learning
  • AI-driven automation solutions

Key Requirements

  • 10+ years professional software engineering or machine learning engineering experience
  • 10+ years specialized experience developing AI/ML solutions for manufacturing automation
  • Deep expertise in LoRA fine-tuning
  • Strong programming skills in Python with proficiency in PyTorch
  • Production experience with full-stack development
  • Expertise in backend development using FastAPI
  • Advanced database engineering skills with PostgreSQL
  • Hands-on experience with Kubernetes deployments
  • Proven experience executing end-to-end automation projects

Work Rights

Not specified

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