Jobs at General Motors

Own the strategy, roadmap, and delivery of secure, passwordless customer authentication across GM web, mobile, and vehicle experiences. Lead adoption of passkeys, biometrics, mobile-to-vehicle authentication, persistent authentication, and risk-based authentication. Partner with engineering, cybersecurity, privacy, legal, design, and vehicle teams to ensure compliant, phishing-resistant experiences. Define authentication KPIs, drive measurable outcomes, manage dependencies, and influence senior leadership across GM’s unified identity ecosystem.

Build and manage large-scale automotive data infrastructure, telemetry pipelines, analytical models, dashboards, and AI/ML solutions. Analyze battery, vehicle electronics, warranty, and diagnostic data to identify patterns, resolve issues, and support vehicle program decisions. Architect Azure Databricks lakehouse solutions, develop diagnostic and prognostic algorithms, automate root-cause analysis, and maintain production software and reporting systems.

Develop 2D and 3D simulation platforms for autonomous mobile robots, create realistic scenarios and edge cases, integrate navigation software, debug simulated robot behavior, analyze results, and build regression testing workflows. The role collaborates with autonomy and AI teams to validate robotic systems and improve simulation capabilities, robustness, and deployment readiness.

Leads the AV Data Processing and Services team, combining hands-on software engineering with people management. Owns architecture and roadmap for petabyte-scale distributed data pipelines, storage, batch inference, streaming, simulation, cloud infrastructure, observability, reliability, and cost optimization. Recruits and mentors engineers, establishes SLAs, manages incidents, and translates cross-functional requirements into dependable technical deliverables.

Leads an engineering team developing autonomous vehicle evaluation platforms, metrics, workflows, dashboards, and analysis tools for simulation and on-road testing. Sets technical direction, guides statistical and machine learning evaluation methods, oversees performance analysis across perception, prediction, and planning, and supports release gating and risk assessment. Responsibilities include hiring, coaching, architectural decisions, cross-functional collaboration, code quality, observability, and translating system-level results into actionable engineering and leadership insights.

Own numerical analysis and model parity for compressed, quantized, and optimized autonomous-vehicle models. Develop Jacobian/Hessian sensitivity tools, connect numerical differences to driving behavior, diagnose training instabilities, and build low-overhead observability for distributed training. Investigate floating-point errors, edge cases, and implementation divergence while translating analytical results into deployment decisions and production-ready tooling.

Leads the Planner Evaluation engineering team for GM Super Cruise, owning technical vision, multi-quarter roadmaps, simulation and on-road validation, metrics, automated workflows, and scalable evaluation platforms. Guides architecture, testing, root-cause investigations, cross-functional requirements, and software quality practices. Mentors engineers and drives technical reviews, reliability, and engineering standards for autonomous driving systems.

Leads enterprise engineering platforms for embedded software, simulation, and cloud workloads. Designs CI/CD, GitOps, Kubernetes, Terraform, progressive delivery, observability, security, and compliance architectures. Establishes branching, release, quality, and engineering standards across teams while improving productivity, release confidence, and product quality. Mentors DevOps and simulation developers and provides hands-on technical leadership for complex, safety-critical software environments.

Design, build, and operate scalable hybrid human/machine data-labeling tools and pipelines for autonomous vehicle ML. Implement full‑stack features (frontend, backend, APIs), integrate ML-driven annotation and active learning, build automation and QA tooling, and own projects end-to-end while collaborating with ML, product, and operations teams to improve labeling velocity and quality.

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

Staff software engineer responsible for designing, building, and operating production authorization services. The role develops role-based, attribute-based, and policy-driven access controls; leads security reviews; builds cloud-native microservices and APIs; establishes engineering standards, observability, and deployment practices; mentors engineers; and supports critical systems through on-call rotations.

Design, develop, deploy, and maintain large-scale data platform services supporting autonomous vehicle model training, mining, labeling, and replay. Lead operational excellence through SLOs, SLIs, incident response, and lifecycle management. Partner with ML and data engineers to build self-service capabilities, deliver end-to-end technical projects, and shape the roadmap. Participate in planning, code reviews, interviews, onboarding, and mentoring while optimizing distributed systems for cost, performance, and reliability.

Leads the architecture, implementation, and operational excellence of DevOps, CI/CD, build, release, and developer productivity platforms for next-generation infotainment systems. Designs scalable embedded Linux build pipelines, automates releases, improves observability, builds self-service tooling, and drives cross-functional initiatives. The role mentors engineers, influences technical direction, and advances software delivery reliability and developer velocity across multiple vehicle programs.

Leads product vision, strategy, roadmaps, and execution for in-vehicle privacy, identity, driver recognition, authentication, and secure personalization. Partners across engineering, design, legal, privacy, cybersecurity, safety, mobile, cloud, and vehicle teams to deliver consistent experiences across vehicles and connected services. Defines consent, privacy controls, profile security, digital-key linking, authentication flows, success metrics, launch plans, and continuous improvements.

Design, develop, and maintain software systems for autonomous driving evaluation workflows. Collaborate across teams, improve infrastructure, and mentor engineers.

Lead camera ISP tuning and image quality evaluation for autonomous vehicle cameras. Collaborate with cross-functional teams and vendors to define specs, characterize sensors, develop ISP configurations, run objective/subjective IQ tests (Imatest), and optimize ISP for perception performance in production vehicles.

Design and deliver production automotive embedded software across MCU and SoC platforms for ADAS HMI experiences. Responsibilities include software architecture, real-time and cross-domain communication, vehicle signal integration, diagnostics, testing, debugging, validation, production launch, tooling improvements, and mentoring. The role requires collaboration across systems, electrical, HMI, ADAS, platform, supplier, and vehicle integration teams while meeting safety, performance, reliability, and maintainability requirements.

Develop Python software and data systems that capture, validate, process, monitor, and deliver autonomous-vehicle telemetry from fleets to cloud and AI development pipelines. Own reliability initiatives, define architectures and operational metrics, debug distributed cloud and backend issues, improve observability and data quality, and apply AI/LLMs to incident triage and root-cause analysis. Collaborate across engineering and operations teams, lead design reviews, deliver tested production solutions, and mentor engineers.

Lead the technical vision, architecture, and roadmap for Galileo, a large-scale simulation platform supporting autonomous-driving development. Design distributed systems for simulation orchestration, test management, result analysis, data processing, visualization, and developer tooling. Drive cross-functional initiatives, improve performance and reliability, establish operational excellence, mentor engineers, and influence architecture across teams. The role requires building scalable production platforms and translating customer needs into effective technical strategies.

Develop scalable backend services, APIs, event-driven workflows, metadata pipelines, configuration tools, deployment controls, and observability for vehicle data collection across fleets. The role owns production systems, improves data quality and campaign monitoring, leads cross-team technical initiatives, and contributes through architecture reviews, testing, code reviews, mentorship, and production support. Collaboration spans AI research, data engineering, vehicle engineering, autonomy, privacy, product, and operations teams.