Note: The job is a remote job and is open to candidates in USA. General Motors is a global leader in advanced driver assistance. They are seeking a Senior Software Engineer to help build and evolve the evaluation ecosystem that powers the development and scaling of GM’s autonomous driving technology.
Responsibilities
Architect and implement metrics and analyses to introspect autonomous driving software performance at interfaces across the autonomy stack; partner closely with autonomy developers and systems engineers
Design and implement analysis algorithms that summarize, aggregate, and cluster metrics produced by simulations and on-road runs of the autonomy stack
Propose and develop new statistical and ML methods to quantify performance and identify patterns of system and subsystem behavior across diverse scenes and operational domains
Develop and apply methods to introspect the operation of ML components in the autonomy stack, including evaluation of perception, prediction, and planning models
Build and maintain autonomy evaluation dashboards and interactive reports that provide clear, explainable insights (e.g., trend analysis, drift detection, scenario coverage) for development, verification, and leadership
Leverage vision-language models (VLMs) and large language models (LLMs), where appropriate, to classify autonomy performance, identify critical scenarios, and prioritize validation efforts, integrating human-in-the-loop review where needed
Maintain a high technical standard through thoughtful system design, code reviews, testing, observability, and adherence to software-engineering best practices
Interface with cross-organizational partners to articulate requirements, resolve handoff issues, and share best practices around evaluation, metrics, and experiment design
Skills
5+ years of applied experience with robotics or autonomous systems software (e.g., sensors, perception, prediction, planning, or control), data analysis, ML evaluation, or autonomy analytics
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
Proficiency with Pandas, NumPy, SciPy, and plotting/visualization libraries for large-scale data analysis and reporting
Comfort working with C++ codebases, including reading, debugging, and instrumenting core algorithms
A strong curiosity to question anomalous data and systematically root-cause discrepancies
Demonstrated technical leadership, including driving architectural decisions, influencing cross-team designs, and owning complex features or services end-to-end
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
Experience in autonomous driving or field robotics, including visualizing and interpreting results from simulation and field experiments
Experience evaluating robotics or AV systems using sensor data (e.g., camera, lidar, radar) and large-scale time-series analysis
Strong intuition for data visualization and the ability to decompose high-dimensional metrics into clear, trustworthy, and consumable views for technical and non-technical audiences
Familiarity with statistical modeling, experimental design, and hypothesis testing for autonomy or simulation evaluation; fluency with Pandas, NumPy, SciPy, and visualization tools
Proficiency in C++ and SQL; experience shaping logging, data schemas, and evaluation pipelines for large-scale autonomy testing and performance monitoring
Experience working with ROS or similar robotics/IPC frameworks, log pipelines, and large-scale experiment databases or evaluation platforms
Prior development experience with computational geometry, linear algebra, PyTorch, and ML techniques applied to perception, prediction, planning, or control
Background in modeling agent interaction and contributing to release gating and safety decisions for autonomy systems
Experience leveraging AI-assisted development and analytics tools to improve productivity and evaluation coverage
Benefits
Benefit options include medical, dental, vision
Health Savings Account
Flexible Spending Accounts
Retirement savings plan
Sickness and accident benefits
Life insurance
Paid vacation & holidays
This job may be eligible for relocation benefits if you are interested in relocating to the bay area.
Hybrid/Remote: This role can be based remotely but if you live within a 50-mile radius of Sunnyvale or Mountain View you are expected to report to that location three times per week.
Company Overview
General Motors is an automotive company that designs, produces, markets, and distributes vehicles and vehicle parts. It was founded in 1908, and is headquartered in Detroit, Michigan, USA, with a workforce of 10001+ employees. Its website is
Company H1B Sponsorship
General Motors has a track record of offering H1B sponsorships, with 338 in 2026, 787 in 2025, 740 in 2024, 450 in 2023, 795 in 2022, 748 in 2021, 452 in 2020. Please note that this does not guarantee sponsorship for this specific role.