Staff AI Engineer

General Motors (GM)

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Sunnyvale, CAAtlanta, GAAustin, TXDetroit, MIWarren, MIMilford, CT
Salary
$189,300–$290,700 / yr
Posted
106 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $204k
This role $240k
$136k most similar roles pay here $307k

This role pays more than 72% of similar roles. Most pay $163,550–$245,112 — the shaded band above. At the midpoint, this role pays about $240k versus about $204k for comparable roles.

Based on 240 similar postings.

Employer

About General Motors (GM)

General Motors (GM) is a leading American multinational automotive corporation founded in 1908 and headquartered in Detroit, Michigan.

General Motors (GM) currently has 116 open roles on FindRole.

Listed pay typically runs $160,200–$245,000 across 59 roles with salary data.

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View all roles at General Motors (GM)

At a glance

TL;DR · Staff AI Engineer

As a Staff AI Engineer on the SimAI team, you will build and deploy applied AI/ML solutions that support simulation workflows, internal tools, and mission-critical engineering use cases. You will manage the full lifecycle of innovation, from early exploration and rapid prototyping to shipping robust production systems. Your daily work involves collaborating with simulation, scenario-generation, data, and engineering teams to identify opportunities where AI can create value. The role focuses on fine-tuning, adapting, optimizing, and evaluating models rather than training foundation models. You will utilize Python, PyTorch, TensorFlow, OpenAI APIs, HuggingFace, gsplat, and other libraries to develop high-performance inference pipelines. Key technical areas include multimodal GenAI, 3D reconstruction, NeRF, Gaussian Splatting, world models, diffusion-based generation, vector search/RAG systems, and integration into robotics or AV perception stacks.

What does a AI Engineer earn in California?

Median $246150 from 84 postings across 12 companies.

See salary data

What you'll do

  • Build and deploy applied AI/ML solutions for simulation workflows and internal engineering tools.
  • Develop robust, high-performance inference pipelines for production systems.
  • Fine-tune, adapt, and optimize state-of-the-art multimodal GenAI and 3D reconstruction models.
  • Integrate machine learning models into simulation pipelines, robotics systems, and mapping workflows.
  • Implement vector search/RAG systems and embedding pipelines to enhance model performance.
  • Manage the full lifecycle of AI projects from initial research exploration to production deployment.
  • Lead multi-quarter technical initiatives and define system architecture with minimal guidance.

What we're looking for

  • Master’s degree required, PhD preferred, in CS, Robotics, EE, or related fields.
  • 8+ years of applied ML/AI engineering experience.
  • 3+ years of experience delivering production AI systems at scale.
  • Deep knowledge of modern multimodal or 3D computer vision pipelines such as NeRF, Gaussian Splatting, or diffusion models.
  • Proficiency in Python and experience with libraries like PyTorch, TensorFlow, HuggingFace, or OpenAI APIs.
  • Experience fine-tuning, optimizing, and deploying foundation models (LLMs, VLMs, or 3D neural models) into production systems.
  • Knowledge of ML fundamentals including data preprocessing, training pipelines, evaluation metrics, and performance optimization.
  • Familiarity with cloud platforms (GCP), Kubernetes, Docker, and vector search/RAG systems.

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