AV Safety Engineering Analytics Lead Engineer (GPSSC)

General Motors

1d•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 AV (Automated Vehicle) Safety Engineering Analytics team is seeking an AV Safety Engineering Analytics Lead Engineer with capabilities at the intersection of automotive engineering, autonomous technology, data science and cloud processing. The AV Safety Engineering Analytics team is the resource supporting teams and stakeholders from around the company to bring a broad range of data and analytics capabilities to bear in AV safety engineering related decision making. This team will maintain proficiency integrating continuously flowing data from vehicle systems, company databases, third-party services, federal and state agencies 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 a senior manager in 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 innovative solutions.

Requirements

Master’s degree in Computer Science, Mechanical Engineering, Vehicle Engineering, Physics, or a related field; or equivalent practical experience
10+ years of experience establishing and conducting large scale analyses of human and/or automated driving performance related data
5+ years in ADAS, autonomous vehicles, robotics or related field
Experience in the following:
Leadership: Demonstrated experience leading teams conducting large scale data analyses to support enterprise decision making. Involvement in enterprise level strategy and roadmap development. Experience using agile methods as well as longer range planning methods. Experience recruiting and retaining talent, developing and motivating employees, conducting goal setting/alignment, conducting performance reviews.
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, applied frequentist methods, applied Bayesian concepts, 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

Provide the strategic vision and manage the design and development of infrastructure that supports safety assurance analytics addressing internal and external stakeholder needs across the phases of automated driving system development and deployment, including both real-world and simulation data.
Oversee the design and integration of contemporary driving safety analytics relevant areas of expertise including AV engineering, AI/ML, large scale processing (cloud), and data science.
Set team objectives, goals and metrics for tracking execution of these goals and delivery of enterprise KPIs.
Oversee the piloting and definition of metrics for the monitoring of development operations and deployment, and establish sufficiency criteria for launch readiness.
Oversee the identification of 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.
Oversee the development of 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.
Oversee the selection of 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.
Oversee the selection of appropriate engineering-, physics-, and driving context-based inputs for the evaluation of AI/ML based analytics models.
Actively engage with partners and seek input, provide technical expertise to inform leadership decision-making, and take ownership of technical projects
Define GM’s data sourcing and processing strategy for AV safety assurance needs, engage externally to influence evolving standards, and contribute to internal and external thought leadership that strengthens GM’s position in the autonomous vehicle ecosystem.
Provide large scale data processing expertise across Global Product Safety, Systems, and Certification activities.
Identify and drive opportunities to improve the efficiency, quality and transparency of safety analytics within GPSSC and across GM.
Mentor and develop team members, fostering a culture of technical excellence and continuous learning.