[Remote] Senior Software Engineer, Autonomy Evaluation
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.
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