Staff Edge AI Engineer — Automotive Multimodal ML

General Motors; Mountain View (CA); Hybrid; USD 189,000 - 291,000; Full time

Benefits offered by this job

Company vehicle program

Relocation benefits

Job summary

General Motors is recruiting a Staff AI/ML Software Engineer to lead adaptation and distillation of foundation models for automotive edge deployment. You will shape the architecture for parameter-efficient fine-tuning, curating datasets, and bridging research with practical vehicle deployment.

Hybrid work model with Mountain View, CA or Seattle, WA base locations; reporting to the office three days per week minimum.

Qualifications

• Bachelor's degree in CS, ML, Data Science, Mathematics, or equivalent practical experience.
• 8+ years of software engineering or applied ML research experience with leadership & architectural decisions.
• Deep proficiency in PyTorch.
• Hands-on experience fine-tuning large language models or vision-language models with demonstrable results.
• Experience with knowledge distillation, PEFT, pruning, or quantization (two of them).

Responsibilities

• Design and build knowledge distillation pipelines for compact edge-deployable models.
• Apply and scale parameter-efficient fine-tuning techniques for cabin interaction models.
• Develop reinforcement learning flywheel with human-in-the-loop alignment (RLHF/DPO).
• Curate and generate datasets to teach smaller models to interpret passenger intent and visual cues.
• Implement Quantization-Aware Training to prevent accuracy loss on hardware.
• Establish evaluation frameworks and benchmarks for fine-tuned models (hallucination, domain accuracy, safety).
• Define base model strategy and justify architecture choices for future deployment.

Skills

Senior ML experience

PyTorch

Fine-tuning LLMs

Knowledge distillation

PEFT

Quantization

Education

Bachelor's degree or higher in CS/ML/DS/Math

Tools

Hugging Face

DeepSpeed

Ray

Megatron

Job description

General Motors is recruiting a Staff AI/ML Software Engineer to lead adaptation and distillation of foundation models for automotive edge deployment. You will shape the architecture for parameter-efficient fine-tuning, curating datasets, and bridging research with practical vehicle deployment.

Hybrid work model with Mountain View, CA or Seattle, WA base locations; reporting to the office three days per week minimum.