AV Safety Engineering Analytics Engineer (GPSSC)

General Motors

2d • Remote

About The Position

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. GM’s vision is zero crashes, zero emissions, and zero congestion—and autonomous vehicle safety is essential to achieving that vision. 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 AV Safety Engineering Analytics team is the resource supporting teams and stakeholders from around the company bring a broad range of data and analytics capabilities to bear in AV safety related decision making. This team will maintain 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 team focuses on continuous up-time proactive analyses as well as supporting specific investigations. If you're passionate about the benefits of autonomous vehicle technology, committed to advancing safety through innovation, and love channeling big data into clear guidance, this role offers exciting opportunities to make a meaningful impact on the future of transportation safety in a dynamic and fun environment. 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, collaborate to develop solutions.

Requirements

• 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
• Experience in the following:
• 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, etc.
• 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 providing large scale and 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 towards learning and self-improvement

Nice To Haves

• 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.

Responsibilities

• Develop data analytics infrastructure that supports safety assurance analytics addressing internal and external stakeholder needs across the phases of automated vehicle development and deployment, including both real-world and simulation data.
• Develop interactive visualizations in support of enhancing transparency and reduction in barriers to source data interrogation.
• Pilot and define metrics for monitoring of 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 a 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 representation 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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level