Senior Manager, AV Evaluation

General Motors (GM)

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: AustinDetroitWarrenMilfordSunnyvale, CA
Salary: $296,300–$453,900 / yr
Posted: 5 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $200k

This role $375k

$106k most similar roles pay here $491k

This role pays more than 99% of similar roles. Most pay $176,775–$223,750 — the shaded band above. At the midpoint, this role pays about $375k versus about $200k for comparable roles.

Based on 239 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 122 open roles on FindRole.

Listed pay typically runs $160,200–$245,500 across 64 roles with salary data.

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At a glance

TL;DR · Senior Manager, AV Evaluation

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Senior Manager - AV Evaluation The Senior Manager - AV Evaluation joins the Evaluation team to build and evolve the ecosystem powering autonomous driving technology development. This leader will own the strategy, roadmap, and operating plan for a critical autonomy evaluation business area encompassing methodology, platforms, and infrastructure. Day-to-day responsibilities include defining end-to-end evaluation strategies for performance, scenario coverage, and risk assessment while leading a high-performing engineering organization through hiring and coaching. The role requires expertise in Python, C++, SQL, and machine learning methods to quantify behavior patterns across various operational domains. Candidates must possess experience in large-scale data processing, workflow orchestration, and infrastructure development. This position solves the complex problem of translating ambiguous validation needs into actionable technical requirements to ensure safety, quality, and release-gating for autonomous systems using sensor data like lidar, radar, and camera.

Skills

Python C++ Machine Learning PyTorch SQL ROS Data Pipelines System Design Time-series Analysis Linear Algebra Computational Geometry Data Visualization Statistical Modeling Infrastructure Workflow Orchestration Observability

What you'll do

Own the strategy, roadmap, and operating plan for the autonomy evaluation business area including methodology, platforms, and infrastructure.
Define end-to-end evaluation strategies for autonomous performance, including scenario coverage, risk assessment, and release-gating readiness.
Drive cross-functional alignment with Autonomy, Simulation, Systems, and Safety teams to translate validation needs into execution plans.
Oversee the development of statistical and machine learning methods to quantify performance and identify behavior patterns across domains.
Manage the development of scalable evaluation infrastructure, including data pipelines, workflow orchestration, and developer tooling.
Build and lead a high-performing engineering organization through hiring, coaching, and establishing clear accountability for technical leaders.
Translate complex system results and platform health signals into actionable feedback for engineering teams and executive leadership.
Manage resource allocation and investment decisions to balance immediate program needs with long-term infrastructure improvements.

What we're looking for

8+ years of experience in robotics, autonomous systems software, data analysis, ML evaluation, or large-scale infrastructure platforms.
5+ years of people leadership experience in complex engineering organizations, including leading managers or senior technical leaders.
Demonstrated ownership of a technical or business area involving strategy, roadmap, execution planning, and cross-functional outcomes.
Experience building production infrastructure for large-scale data processing, workflow orchestration, and service reliability.
Experience developing Python/C++ in production environments including testing, performance, and code review.
Experience evaluating dynamic systems using numerical, statistical, or machine learning methods.
Ability to translate complex technical findings into clear communication for executive and cross-functional audiences.
Bachelor’s, Master’s, or PhD in Computer Science, Robotics, Engineering, Data Science, or a related field (or equivalent experience).

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