Staff Software Engineer, Autonomy Evaluation

WhatYou’llDo

Define the strategy and architecture for metrics and analyses to evaluate autonomous driving software performance across the autonomy stack.

Lead cross-functional efforts with autonomy, systems engineering, simulation, and data teams to embed evaluation into development workflows and release decisions.

Invent and drive new statistical and ML methods, and ML introspection techniques, to quantify performance, detect regressions, and reveal patterns of system behavior at scale.

Own and refine key AV evaluation metrics and KPIs used for readiness and safety decisions; synthesize and present results and tradeoffs to stakeholders; make insights readily available to partner teams through interactive dashboards.

Your Skills and Abilities (Required Qualifications)

7+yearsapplied experience with robotics or autonomous systems software, spanning multiple subsystems fromperceptionthrough planning and control of the vehicle.

3+ years leading evaluation of complex dynamic systems using numerical and ML approaches on large-scale time series data.

Proficiencydeveloping Python in production team environments; strong ability to work in large C++ autonomy codebases.

Proven cross-team technical leadership, including defining strategies adopted by multiple teams and influencing system and architecture decisions.

PhD, Masters, orBachelor’s degree in Computer Science, Robotics, Mechanical or Aerospace Engineering, Machine Learning, ora relatedfield.

What Will Give You a Competitive Edge (Preferred Qualifications)

Experience in autonomous driving or high-stakes field robotics; designing, running, and interpreting large-scale simulation and field experiments.

Deep familiarity with statistical modeling, experimental design, and hypothesis testing for autonomy evaluation; command of Pandas, NumPy, SciPy, and visualization libraries.

Proficiencyin C++ and SQL, and experience shaping logging, data schemas, and evaluation pipelines for large-scale autonomy testing.

Experience working with ROS or other IPC, robotics stack logging, and with large-scale experiment databases, including designing or scaling evaluation platforms.

Priordevelopment with computational geometry, linear algebra,PyTorch, and machine learning.

Background in modeling agent interaction and owning or designing release gating criteria and processes for autonomy systems.

Hybrid:

This role is categorized as hybrid. This means the successful candidate is expected to report to the Sunnyvale or Mountain View office three times per week.

*This job may be eligible for relocation benefits if you are interested in relocatingto the bay area.

Compensation

The salary range for this role is $185,00 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 incentivepayprogram offers payouts based on company performance, job level, and individual performance.

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, tuitionassistanceprograms, employeeassistanceprogram, GM vehicle discounts and more.

Company Vehicle

Upon successful completion of a motor vehicle report review, you will be eligible toparticipatein a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participantsare required topurchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.

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This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.



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Benefits Overview

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