Senior Software Engineer, Autonomy Evaluation

General Motors; Sunnyvale (CA); On-site; USD 100,000 - 130,000; Full time

Job summary

General Motors in Sunnyvale, California, is seeking a candidate to design algorithms for analyzing and visualizing data in autonomous vehicle technology. As part of the Evaluation team, you will work on developing metrics and dashboards to enhance data-driven decisions in AV development.

Applicants should have 3+ years of experience in data analysis and ML evaluation, along with a Bachelor's degree in a related field. Proficiency in data analysis tools like Pandas and NumPy is essential. Join us to help shape the future of personal autonomous vehicle experiences.

Qualifications

• 3+ years applied experience in data analysis, ML evaluation, or autonomy analytics.
• Proficiency with Pandas, NumPy, SciPy, and plotting/visualization libraries.

Responsibilities

• Design and implement analysis algorithms to summarize, aggregate, and cluster metrics.
• Build and maintain GM's primary autonomy evaluation dashboards and reports.
• Leverage vision-language models to classify autonomy performance.

Skills

Data analysis

Machine Learning evaluation

Statistical methods

Education

Bachelor's or higher degree in Computer Science, Data Science, Mechanical or Aerospace Engineering

Tools

Pandas

NumPy

SciPy

Job description

Job Description

The Role:

General Motors is a global leader in advanced driver assistance. With Super Cruise hands-free technology in more than 500,000 Super Cruise-equipped vehicles on the road, and over 700 million hands?free miles driven, GM is proving that automation can be trusted, intuitive, and helpful. GM has the global reach to bring cutting?edge advances to everyday drivers at an unprecedented scale. Join us to help deliver the next generation of safe and delightful personal autonomous vehicle experiences.

About the Organization:

The Evaluation team builds and evolves the evaluation ecosystem that powers developing and scaling 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, and help accelerate validated AV deployment at scale.

What You'll Do

• Designand implementanalysis algorithmsthatsummarize,aggregate,and clustermetrics produced by simulations of the autonomy stack
• Build andmaintainGM's primary autonomyevaluationdashboards and reportsthat provide clear, explainable insights to engineering and leadership, including trend analysis, drift detection, and scenario coverage.
• Leveragevision-language models (VLMs)andlarge language models (LLMs)to classify autonomy performance,critical scenarios, and prioritize validation efforts, integrating human-in-the-loop whereappropriate.
• Maintain a high technical standard through architectural design, code reviews, and by following software-engineering best practices.
• Interface with cross-org partners to articulate requirements, resolve handoff issues, and share best practices.

Your Skills & Abilities (Required Qualifications)

• 3+yearsapplied experience indata analysis, ML evaluation, or autonomy analytics, working with large-scale datasets and statistical methods.
• ProficiencywithPandas,NumPy,SciPy,and plotting/visualization libraries.
• Bachelor's or higher degree inComputer Science,Data Science,Mechanical or Aerospace Engineering, or equivalent practical experience.

What Will Give You a Competitive Edge (Preferred Qualifications)

• A strong understanding of how to visualize quantitative information effectively and transparently.The ability to decompose a multi-dimensional space into something consumable.
• Experience evaluatingroboticssystemsor autonomous vehicles, including sensor data (camera, lidar, radar) and time-series analysis.
• A strong curiosity to question anomalous data and root-cause discrepancies

#GM-AV-1

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