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AV Safety Engineering Analytics Engineer (GPSSC)General Motors • Honolulu, Hawaii, United States
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AV Safety Engineering Analytics Engineer (GPSSC)

General Motors
  • US
    Honolulu, Hawaii, United States
  • US
    Honolulu, Hawaii, United States
Apply Now

About

Job Overview Work arrangement: Remote. This role is based remotely but if you live within a 50-mile radius of Atlanta, Austin, Detroit, Warren, Milford or Mountain View, you are expected to report to that location three times per week, at minimum.
The Safety Assurance for Effective Autonomous Driving Software (SAFE-ADS) department is part of GM's Global Product Safety, System, and Certification (GPSSC) organization. Our mission is to help GM deliver trustworthy automated driving products. As the central authority for automated driving system (ADS) safety, SAFE-ADS brings together experts from across the company to develop and maintain a comprehensive safety case including safety performance indicators for GM's automated driving technologies.
The Role The AV Safety Engineering Analytics team is seeking an AV Safety Analytics Engineer with capabilities at the intersection of automotive engineering, data science, and cloud processing. The team supports teams and stakeholders across the company, bringing a broad range of data and analytics capabilities to AV safety related decision making. The role maintains proficiency integrating continuously flowing data from vehicle systems, company databases, third-party services, federal agencies and state DOTs to inform system design and quantify driving performance. The focus is on continuous up‑time proactive analyses as well as supporting specific investigations.
As part of the AV Safety Engineering Analytics team, you will work closely with cross‑functional partners and internal customers to prototype, define, and productionize performance metrics and sufficiency criteria. You will engage deeply with stakeholders to understand their challenges and needs, and collaborate to develop solutions.
What You'll Do
Develop data analytics infrastructure that supports safety assurance analytics addressing internal and external stakeholder needs across phases of automated vehicle development and deployment, including real‑world and simulation data.
Develop interactive visualizations to enhance transparency and reduce barriers to source data interrogation.
Pilot and define metrics for monitoring development operations and deployment, and establish sufficiency criteria for launch readiness.
Identify relevant data for supporting safety monitoring and the development of a reliable supply chain of continuously flowing data from a variety of sources (internal and external) to support safety assurance related activities.
Develop cloud‑based continuous up‑time analytics pipelines that manage data from raw form, through analyses, and into browser‑based interactive visualizations and periodic reporting artifacts.
Select appropriate engineering‑ and physics‑based signal processing, sampling, filtering, smoothing, etc., to prepare raw signals for analyses and/or storage in a down‑sampled form.
Integrate and transform data streams to construct physically meaningful representations of vehicle motion, driving context, and intermediate system performance, including reduction of time‑series representations to features.
Apply engineering domain expertise to distinguish erroneous sensor data from real outliers.
Optimize code for efficiency and package for automated cloud‑based execution.
Your Skills & Abilities (Required Qualifications)
Bachelor's degree in Computer Science, Mechanical Engineering, Vehicle Engineering, Physics, or a related field; or equivalent practical experience.
5+ years of experience in large‑scale data analyses of human and/or automated driving performance related data.
5+ years in ADAS, autonomous vehicles, robotics or related field.
Programming & frameworks: Python, SQL.
Cloud & Big Data: Extensive experience in cloud‑based large scale process including notifications, queuing, serverless cloud functions, event‑driven processing, code as infrastructure, containerization, process monitoring, process optimization, identity and access management, service‑to‑service access.
Statistics: Working familiarity with descriptive statistics, managing bias in large data mining activities, experimental design, sampling strategies.
Dev Ops and Infrastructure as Code: CI/CD, versioning, Docker & Kubernetes, GitHub, Jira, Jenkins, Poetry, Terraform.
Data Analysis & Visualization: Tableau, PowerBI, Plotly/Dash, Shiny, Pandas, NumPy.
Proven track record of delivering large‑scale continuous analytics development and deployment.
Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
Strong problem‑solving mindset and a proactive attitude toward learning and self‑improvement.
What Will Give You A Competitive Edge (Preferred Qualifications)
Experience in processing and analyses of large‑scale vehicle motion and context related data to characterize driving performance.
Record of involvement in vehicle safety related discourse through conference participation or publications.
Additional Information 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 job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate.
This role is categorized as remote. 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. The selected candidate will be required to travel less than 25% for this role.
Equal Employment Opportunity Statement General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers. All employment decisions are made on a non‑discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.
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  • Honolulu, Hawaii, United States

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  • English
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