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

General Motors develops vehicles, software, and safety technologies that support safer, smarter, and more connected mobility. The Safety Data Analysis Engineer will provide data-driven engineering support for autonomous-vehicle operational safety and issue response by investigating potential issues, integrating event-related data, performing root-cause analyses, and delivering evidence for safety decisions.

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

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
• The selected candidate will be required to travel <25% for this role
• This role is categorized as remote. This means the selected candidate may be based anywhere in the country of work and is not expected to report to a GM worksite unless directed by their manager
• This job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate
• GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc)
• 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