General Motors

Engineering Manager - Autonomy Evaluation

General Motors • $185K — $284K *
Sunnyvale, CA 94087Hybrid
Manufacturing & Automotive
8 - 10 years of experience
3 days ago
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Job Overview by Ladders

Qualifications

  • 8+ years of experience in robotics, autonomous systems software, data analysis, or related fields, including team leadership.
  • 3+ years in evaluating dynamic systems using numerical or ML approaches, particularly with time-series data.
  • Strong proficiency in Python for production environments, including testing and performance aspects.
  • Hands-on familiarity with data analysis libraries like Pandas and NumPy for large-scale evaluations.
  • Ability to read and debug C++ codebases, with an understanding of core algorithm instrumentation.
  • Proven technical leadership capability, including architectural decision-making and cross-team influence.
  • Strong analytical skills to root cause data anomalies.

Responsibilities

  • Lead and mentor a team of engineers in developing autonomy evaluation platforms and analysis tools.
  • Set the technical direction for systems that assess autonomous driving performance.
  • Design and deliver algorithms to summarize and analyze metrics from simulation and on-road tests.
  • Guide the development of statistical and machine learning methods for performance evaluation.
  • Oversee explainable and scalable evaluation methods for machine learning components in autonomy systems.
  • Ensure delivery of clear dashboards and reports for trend analysis and insights.
  • Collaborate with cross-functional teams to align on evaluation strategies and requirements.

Benefits

  • Comprehensive health and wellbeing benefit programs including medical, dental, and vision coverage.
  • Health Savings and Flexible Spending Accounts along with retirement savings plans.
  • Life insurance, sickness, and accident benefits available.
  • Paid vacation and holidays with tuition assistance programs.
  • Discounts on GM vehicles as part of employee benefits.
Full Job Description
Job Description

The Evaluation team builds and evolves the evaluation ecosystem that powers the development and scaling of GM's autonomous driving technology. We develop metrics, automated workflows, and analysis approaches that enable data-driven decisions across AV development and verification. Partnering with Autonomy, Simulation, Systems, and Safety teams, we act as system-level integrators and arbiters of end-to-end AV quality.

We own large-scale test scenario libraries, continuous evaluation pipelines, and critical risk assessment and release-gating components, treating road testing, data mining, training, and metrics as first-class use cases in a unified analytics framework. By joining this team, you will help shape GM's core evaluation platforms, turn system-level results into clear feedback for engineering and leadership, and help accelerate validated AV deployment at scale.

We are looking for an Engineering Manager to lead a team building the software, metrics, and analysis systems used to evaluate autonomous driving performance at scale. This leader will combine strong technical judgment with people leadership, cross-functional influence, and execution rigor to help shape GM's core evaluation platforms and accelerate validated AV deployment.

What You'll Do (Responsibilities)
  • Lead, coach, and grow a team of engineers building autonomy evaluation platforms, metrics, workflows, dashboards, and analysis tooling for simulation and on-road testing.
  • Set technical direction for systems that introspect autonomous driving software performance across interfaces and across the autonomy stack.
  • Drive the design and delivery of analysis algorithms that summarize, aggregate, and cluster metrics from simulation and on-road runs.
  • Guide the team in developing new statistical and machine learning methods to quantify performance and identify behavior patterns across scenes and operational domains.
  • Oversee evaluation approaches for ML components across perception, prediction, and planning, ensuring methods are explainable, scalable, and useful to development and verification teams.
  • Ensure the team delivers clear dashboards and interactive reports for trend analysis, drift detection, scenario coverage, and leadership insight.
  • Partner closely with Autonomy, Simulation, Systems, and Safety teams to define requirements, resolve handoff issues, and align evaluation strategy with product and release needs.
  • Help the organization leverage emerging AI techniques, including VLMs and LLMs where appropriate, to classify autonomy performance and prioritize validation work with human-in-the-loop review.
  • Maintain a high technical bar through strong system design, code review, testing, observability, and engineering best practices.
  • Translate system-level results into clear feedback for engineering and leadership and drive execution against high-priority evaluation outcomes.


Leadership Responsibilities
  • Build a high-performing, inclusive engineering team through hiring, coaching, feedback, and career development.
  • Create clarity across priorities, roadmaps, and dependencies for a technically complex evaluation domain.
  • Balance near-term delivery with long-term platform investments in metrics, tooling, and infrastructure.
  • Raise the quality of team execution through clear ownership, strong design reviews, and healthy operating mechanisms.
  • Represent the team effectively across partner organizations and influence decisions that affect system-level AV quality.


Your Skills & Abilities
  • 8+ years of relevant experience in robotics, autonomous systems software, data analysis, ML evaluation, or autonomy analytics, including substantial experience leading technical teams and delivering complex software systems. This manager version is adapted from a senior IC profile that calls for 5+ years in these domains.
  • 3+ years evaluating dynamic systems using numerical and/or ML approaches, including time-series data, state derivatives, dynamics, and interconnected subsystems.
  • Strong proficiency developing Python in production team environments, including testing, performance, and code review.
  • Strong hands-on familiarity with Pandas, NumPy, SciPy, and data visualization libraries for large-scale analysis and reporting.
  • Comfort working with C++ codebases, including reading, debugging, and instrumenting core algorithms.
  • Demonstrated technical leadership, including driving architectural decisions, influencing cross-team designs, and owning complex services or platforms end-to-end.
  • Strong cross-functional communication and an ability to convert ambiguous evaluation needs into clear technical plans.
  • Strong analytical curiosity and a disciplined approach to root-causing anomalous data and system discrepancies.
  • Bachelor's, Master's, or PhD in Computer Science, Robotics, Mechanical or Aerospace Engineering, Machine Learning, Data Science, or a related field, or equivalent practical experience.


What Will Give You A Competetive Edge
  • Experience in autonomous driving or field robotics, including interpreting results from simulation and field experiments.
  • Experience evaluating robotics or AV systems using sensor data such as camera, lidar, and radar, and working with large-scale time-series analysis.
  • Strong intuition for data visualization and the ability to turn high-dimensional metrics into clear, trustworthy views for technical and non-technical audiences.
  • Familiarity with statistical modeling, experimental design, and hypothesis testing for autonomy or simulation evaluation.
  • Proficiency in SQL and experience shaping logging, data schemas, and evaluation pipelines for large-scale autonomy testing and performance monitoring.
  • Experience with ROS or similar robotics/IPC frameworks, log pipelines, and experiment databases or evaluation platforms.
  • Prior experience with computational geometry, linear algebra, PyTorch, and ML techniques applied to perception, prediction, planning, or control.
  • Background contributing to release gating, risk assessment, and safety-related decisions for autonomy systems.
  • Experience using AI-assisted development and analytics tools to improve engineering productivity and evaluation coverage.


Compensation

  • The salary range for this role is $185,100 and $284,100. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.


  • Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.


Benefits

  • Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.


Company Vehicle
  • Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies."


About General Motors

General Motors Company engages in the manufacture and sale of cars and trucks in the United States, China, Brazil, Germany, the United Kingdom, Canada, and Italy. It offers sedans, crossovers, sport utility vehicles, pick-up trucks, coupes, sports/convertibles and hybrid vehicles, hatchbacks/wagons, and vans, as well as mini cars in India. The company also provides parts and accessories, such as iPod and MP3 compatibility, mobility accessories, performance parts, AC parts and services, and merchandise. In addition, it offers vehicle safety, security, and information services. The company provides used vehicles. It offers its products through dealers and distributors. General Motors Company was formerly known as NGMCO, Inc. and changed its name to General Motors Company in July 2009. The company was incorporated in 2009 and is based in Detroit, Michigan. It operates manufacturing facilities in India, the United States, and Canada. General Motors Company operates as a subsidiary of the United States Department of The Treasury. General Motors led global vehicle sales for 77 consecutive years from 1931 through 2007, longer than any other automaker, and is currently among the world's largest automakers by vehicle unit sales. General Motors acts in most countries outside the USA via wholly-owned subsidiaries but operates in China through 10 joint ventures. GM's OnStar subsidiary provides vehicle safety, security, and information services. In 2009, General Motors shed several brands, closing Saturn, Pontiac, and Hummer, and emerged from a government-backed Chapter 11 reorganization. In 2010, GM made an initial public offering IPOs to date and returned to profitability later that year.

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Learn more about General Motors
Size
157,000 employees
Market Cap
$46.9 billion
Industry
Manufacturing & Automotive
Net Income
$6.4 billion
Founded
1908
5 Year Trend
-3.2%
Revenue
$122.4 billion
NASDAQ
GM
* Ladders Estimates

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