Jobs at General Motors

Leads the Metrics Frameworks team supporting autonomous vehicle evaluation. Responsibilities include managing software and data engineers, setting technical strategy and roadmaps, delivering scalable metrics and data-processing platforms, improving reliability and observability, balancing platform investments and technical debt, and partnering with stakeholders. The role also oversees architecture, testing, operational excellence, incident response, and production support for simulation and real-world driving data systems.

Develop scalable backend services, APIs, event-driven workflows, metadata pipelines, and observability tools for vehicle data collection across autonomous vehicle fleets. Design configuration, deployment, monitoring, and version-reconciliation workflows while ensuring data quality, privacy, traceability, and operational reliability. Lead cross-functional technical initiatives, contribute to architecture and testing, provide production support, and mentor engineers.

Leads regional and global sourcing for technology purchases, including software, SaaS, and infrastructure. Develops sourcing strategies, negotiates commercial and legal terms, manages supplier relationships and performance, supports renewals, benchmarks markets, resolves supplier issues, and coordinates with IT, Engineering, Security, Privacy, Legal, and business stakeholders. The role requires managing multiple sourcing projects, maintaining continuity, and making strategic purchasing recommendations. Travel is approximately 10% domestically and internationally.

Provides technical leadership for scalable cloud, data, and AI foundations supporting mapping databases and software-defined vehicle experiences. Designs data platforms, pipelines, APIs, governance, observability, and reusable cloud-native services. Builds production-ready Agentic AI solutions using retrieval, orchestration, tool integration, access controls, evaluation, and human oversight. Partners across engineering teams, leads architecture and design reviews, establishes reusable standards, mentors engineers, and drives secure, reliable, cost-efficient adoption of cloud, data, and AI capabilities.

Designs, develops, and operates secure, scalable Java and Spring Boot microservices, REST and GraphQL APIs, and event-driven integrations for GM mobile platforms. Deploys cloud-native services on Azure, strengthens CI/CD and DevOps automation, and improves observability, reliability, and service health. Applies AI-enabled engineering practices, TDD, and automated testing. Partners cross-functionally on architecture and delivery while mentoring engineers and maintaining technical documentation, runbooks, and engineering standards.

Build scalable evaluation, introspection, visualization, and metrics tools for autonomous vehicle machine-learning models. Develop workflows processing billions of examples, connect offline evaluation with data and training decisions, and support model-based metrics, simulation, and launch decisions. Collaborate with modeling, data, infrastructure, and validation teams while contributing to design reviews, code reviews, and production software delivery.

Conduct organizational and workforce research using advanced statistical, causal, longitudinal, multilevel, survey, and mixed-method analyses. Study employee experience, engagement, sentiment, workforce dynamics, and intervention effectiveness using employee and HR data. Lead projects from research design through recommendations, communicate findings to technical and executive audiences, develop reusable methods and analytical products, and maintain reproducible, well-documented work while protecting sensitive employee data.

Serve as the senior technical authority and system architect for GM’s vehicle Core OS platform. Define architecture and roadmap for hypervisors, virtualization, operating-system integration, safety partitioning, secure boot, containers, workload management, and platform services. Lead performance optimization, technology selection, supplier relationships, complex root-cause investigations, cross-functional technical programs, architecture reviews, and engineering standards. Mentor senior engineers and guide multi-team development of production-grade, safety-critical vehicle compute systems.

Lead the architecture and development of GM’s vehicle Core OS virtualization platform across embedded Linux, Android, and QNX. Own hypervisor integration, virtual machines, resource partitioning, secure boot, container runtimes, health monitoring, fault recovery, and low-level performance debugging. Build reliable platform services for automotive systems, improve CI/CD and hardware-in-the-loop validation, and collaborate across silicon, BSP, safety, and cybersecurity teams. Mentor engineers and provide technical leadership for production-grade embedded software.

Leads the architecture and development of scalable backend services and software products for GM Commercial Services. Responsibilities include solving complex technical problems, designing reliable systems and APIs, improving engineering practices, writing code and tests, monitoring systems, launching products, collaborating across teams, and mentoring engineers. Requires extensive experience with Java, Kotlin, or Python; databases; cloud platforms; Databricks; and modern web technologies.

Build and lead GM’s Core OS engineering organization for vehicle compute platforms. Own the roadmap and delivery of hypervisors, virtualization, secure boot, safety monitoring, container management, and shared Linux, Android, and QNX environments. Hire engineers, define architecture and interfaces, establish platform KPIs, manage vendors, and deliver production milestones across vehicle programs. Partner with silicon, cybersecurity, functional safety, application platform, and program teams while driving cross-functional execution and large-scale embedded software releases.

Recruits interns, co-ops, recent graduates, and other early-career talent across technical and business roles. Manages requisitions through sourcing, screening, interviews, offers, and pre-employment activities. Builds university and candidate pipelines, coordinates campus engagement, partners with hiring managers and HR, maintains recruiting data in Workday and related systems, and uses recruiting metrics to improve processes and candidate experiences.

Leads development and maturation of optical film stacks and light-management technologies for automotive LCD and OLED displays. Evaluates films, performs optical simulations and measurements, analyzes brightness and display-quality data, resolves optical defects, and collaborates with suppliers and display manufacturers. Establishes characterization and validation methods while supporting material qualification, risk reduction, manufacturability, and transition of validated optical solutions into production vehicle programs.

Owns full-stack vehicle software insight systems across NextJS and Go, from data ingestion through production interfaces. Builds data visualizations and dashboards, extends shared component libraries, collaborates with product, design, and engineering partners, and drives architecture, testing, reliability, and technical direction. The role also includes mentoring engineers, managing concurrent deliverables, and making pragmatic decisions amid changing priorities.

Build and own scalable hybrid human/machine data-labeling platform for autonomous vehicles. Define roadmap, design APIs/UIs, integrate ML-driven annotation, improve data quality, and ship full-stack features across frontend, backend, and ML services.

Designs and develops scalable Golang software supporting enterprise data architecture. Leads technical architecture for complex distributed systems, collaborates across teams, mentors engineers, drives problem solving, and contributes to SAFe delivery practices. Responsibilities include code reviews, testing, CI/CD, deployment, operational support, and long-term technical strategy. The role requires expertise in high-performance software development, enterprise data architecture, concurrency, performance optimization, and cross-functional technical leadership.

Conduct advanced AI and machine learning research for autonomous driving, designing and prototyping state-of-the-art algorithms. Shape technical roadmaps, mentor researchers, collaborate with engineering teams, and represent GM through publications, patents, and conference participation.

Leads and grows an engineering team responsible for developer productivity and observability platforms. Defines technical strategy, oversees distributed-system architecture, guides instrumentation and telemetry practices, supports incident response, and partners with AI/ML, firmware, and infrastructure teams. Leads development of scalable internal tools and data pipelines while managing third-party observability vendors, costs, and relationships.

Lead development of behavior validation products and dashboards for autonomous vehicle software releases. Partner with engineering, safety, and product teams to define roadmaps, metrics, and priorities using data-driven analysis. Build scalable, reliable validation tools with Python, connect data pipelines to user interfaces, and drive cross-functional improvements in safety-critical simulation and validation environments.

Design, implement, benchmark, and optimize CUDA-based GPU kernels and custom operators for on-vehicle ML inference. Build profiling/debugging tooling, integrate kernels into the ML runtime, collaborate with cross-functional teams, and deliver production-grade high-performance libraries meeting strict latency, throughput, and reliability targets.