Senior AI/ML Capacity Engineer

General Motors (GM)

Remote Hybrid

Quick summary

Work type: Remote
Location: Remote
Salary: $144,700–$261,300 / yr
Posted: 73 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $212k

This role $203k

$131k most similar roles pay here $277k

This role pays less than 63% of similar roles. Most pay $176,937–$246,150 — the shaded band above. At the midpoint, this role pays about $203k versus about $212k 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 126 open roles on FindRole.

Listed pay typically runs $170,000–$258,500 across 75 roles with salary data.

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View all roles at General Motors (GM)

At a glance

TL;DR · Senior AI/ML Capacity Engineer

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GM seeks a Senior Capacity Engineer for its AV Infrastructure org’s Capacity and Performance Engineering team, focusing on developing technical models for capacity planning and building automated analytical tools to monitor demand signals. This role involves collaborating with AI/ML engineering teams and cloud vendors to optimize infrastructure and reduce costs while providing strategic input into large-scale ML infrastructure decisions. The ideal candidate has 8+ years of relevant experience, proficiency in Python, Pandas, NumPy, Looker, BigQuery, and distributed systems, along with strong communication skills and experience in cross-functional project execution. This position addresses the critical need for efficient cloud budget management and capacity planning in GM’s autonomous vehicle development efforts.

Skills

Python Pandas NumPy BigQuery Looker Git Linux GCP CI/CD Docker Kubernetes Prometheus SQL Forecasting BI platforms Modern ML system architecture Capacity planning Data modeling

What you'll do

Develop and refine technical models for capacity planning in AV infrastructure.
Design and build automated tools for monitoring capacity and demand signals.
Identify and drive optimization projects to enhance engineering and cost efficiencies.
Partner with AI/ML, infrastructure, and cloud vendors to execute optimization initiatives.
Analyze billing and usage data in GCP to forecast capacity demand accurately.

What we're looking for

8+ years of relevant work experience in cloud infrastructure and capacity planning.
Bachelor's Degree in Computer Science or related field, or equivalent work experience.
Proficient in Python, Pandas, NumPy, Looker, and BigQuery.
Experience with data modeling, SQL on large datasets, and distributed systems.
Good understanding of modern ML system architecture and design.
Ability to execute cross-functional projects and analyze billing/usage data in GCP.
Strong communication skills for partnering with engineering teams and vendors.

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