Safety Data Analysis Engineer – AV Operational Safety and Issue Response (GPSSC)

General Motors

4d•$129,400 - $198,400•Remote

About The Position

The AV Safety Engineering Analytics team is seeking an experienced Safety Data Analysis Engineer to provide engineering support for AV Operational Safety and Issue Response. This is a safety engineering role focused on data-driven issue response and investigation. You will combine engineering judgment, safety analysis, and strong data skills to investigate potential issues, organize event-related data, and develop evidence that supports AV Safety Assurance and AV Operational Safety decisions. The role is designed for an engineer who is highly proficient in navigating, integrating, designing, and analyzing large-scale data. You will support rapid, highly iterative investigations involving specific vehicles, locations, software releases, event sequences, operational conditions, and other issue-relevant dimensions. The scale of AV operations, including potential issues, actual events, readiness drills, and ongoing software releases, creates a need for rapid, detailed, event-driven analyses. At the same time, you will help convert repeatable investigation patterns into reusable analytics and issue-detection methods.

Requirements

Bachelor’s degree in engineering, physics, applied mathematics, or a related physical science.
5+ years of relevant professional experience analyzing large-scale time-series, telemetry, vehicle, robotics, or other engineering data, including working with Robot Operating System (ROS) logs.
Strong working knowledge of Python and SQL.
Experience with time-series analysis, including signal decomposition, filtering, smoothing, sampling, feature construction, or related signal-processing methods.
Experience designing and executing ad hoc analyses while recognizing opportunities to develop scalable, repeatable analytical methods.
Experience gathering analytical requirements, defining data needs, selecting appropriate methods, and communicating findings to partner teams.
Strong problem-solving skills and the ability to work effectively in fast-moving, ambiguous, and highly iterative investigations.
Strong communication and collaboration skills, with the ability to craft fact-based reports through individual and collaborative work across safety, operations, human factors, data engineering, and emerging-issues teams.

Nice To Haves

Experience in autonomous vehicles, advanced driver-assistance systems, robotics, transportation safety, or a related domain.
Experience performing AV- or SDV-specific issue detection, anomaly detection, event investigation, or root-cause analysis.
Experience analyzing large-scale vehicle motion, driving context, automated-driving performance, or operational data.
Experience developing safety performance indicators, safety monitoring methods, or evidence used in safety assurance and operations decisions.
Experience working with cloud-based data platforms, distributed processing, or large-scale analytics workflows.
Experience with BigQuery or comparable cloud data platforms.
Familiarity with C++ or C++-based robotics and vehicle software environments.
Experience with Docker, Kubernetes, GitHub, CI/CD, version control, or related software-development workflows.
Experience collaborating with human-factors, operations, systems, validation, verification, or safety-assurance teams.
Publications, conference participation, or other demonstrated engagement in vehicle safety, robotics safety, safety analytics, or related technical work.

Responsibilities

Respond collaboratively to AV Safety Strategy and Assurance and AV Operations requests for potential issue-specific analyses, event-related data organization, and root-cause investigations.
Collaborate with Engineering, Operations, and Safety teams to investigate potential AV issues and conduct root-cause analyses.
Translate investigation needs into clear analysis requirements, data requirements, analytical designs, and execution plans in collaboration with requesting teams.
Establish and support rapid incident-response and targeted-analysis capabilities that leverage standing data pipelines as well as unique issue- and incident-relevant data sources.
Integrate vehicle telemetry, time-series signals, event and incident records, readiness-drill data, software-release information, location and operational context, and other relevant sources into analysis-ready datasets.
Distinguish data-quality, sensor, instrumentation, and pipeline issues from meaningful operational outliers using engineering judgment and data validation methods.
Deliver concise, technically rigorous analysis findings, readouts, and evidence that help partner teams assess potential operations safety issues and determine appropriate next steps.
Identify investigation workflows that can be generalized into reusable metrics, detection methods, pipelines, or analysis tooling without losing the flexibility required for issue investigation.
Apply engineering and physics-based methods, including signal decomposition, filtering, smoothing, sampling, and feature construction, to transform noisy signals into physically meaningful representations of vehicle behavior and system performance.