Jobs at General Motors

Lead end-to-end machine learning solutions for autonomous driving, mentor engineers, design advanced models, and ensure safety and reliability in diverse scenarios.

The Staff ML Engineer will design and implement backend components for the ML Inference Platform, ensuring efficient model serving and collaborating with ML teams to enhance AI infrastructure at GM.

The Senior Systems Data Scientist will develop methodologies for measuring trust in AV testing, manage data analysis frameworks, collaborate with teams, and provide insights for decision-making.

Design and develop WiFi software for a vehicle communication system, collaborating with hardware and cloud teams to ensure reliability and performance.

Develop and deploy machine learning solutions for autonomous vehicles, mentoring engineers and collaborating on model implementations.

Lead requirements development, system design, and validation for fault management in autonomous vehicle software. Analyze data, prototype validation methods, and mentor team members.

Design and develop cellular software for a Linux-based vehicle communication system, collaborating with hardware teams to ensure reliability and performance.

Lead the design, implementation, and deployment of scalable ML infrastructure for autonomous driving. Drive technical projects, mentor others, and collaborate with teams to enhance ML workflows.

The Staff Software Engineer will design, develop, and optimize large-scale cloud software systems, focusing on user-centric solutions and performance. Responsibilities include system architecture, hands-on coding, and cross-functional collaboration, leveraging modern software practices and technologies.

As a Staff Research Scientist, you'll design advanced algorithms in machine learning, mentor others, and influence technical roadmaps for autonomous driving.

Lead research on machine learning validation for robotics and autonomy systems, focusing on simulation, uncertainty modeling, and creating functional prototypes for testing.

Design and implement GPU-accelerated sensor simulation systems for autonomous vehicles, focusing on real-time rendering performance and efficiency.

As a Staff ML Infra Engineer, you will develop and deploy offboard machine learning solutions for autonomous vehicles, ensuring model integration and performance across teams. You'll build ML infrastructure, implement CI/CD pipelines, support data curation, and mentor engineers.

As a Principal Software Engineer, you will oversee Body Controls software compliance, guide design implementation, mentor engineers, and define compliance strategies.

As a Senior Robotics Engineer, you will develop vehicle dynamics and controls software for GM's Super Cruise system, lead technical reviews, establish validation strategies, and ensure high-quality software delivery through best practices and teamwork.

Build and enhance internal ML tooling to analyze and optimize model distillation, training, and inference. Collaborate with AV engineering and hardware teams to profile performance on GPUs and in-car compute, develop workflows for correctness and efficiency, trace distributed training jobs, and influence model architecture decisions.

Lead strategy and execution for GM's external vehicle APIs, owning roadmaps, requirements, and success metrics. Partner with engineering, design, legal, cybersecurity, and GTM teams to build scalable, secure telematics and vehicle command APIs, expand into global markets, and ensure compliant external data sharing.

Plan, execute, and report autonomous vehicle test scenarios; perform basic triage and data analysis; validate integrations and builds; maintain test documentation and traceability; support test tools, pipelines, and defect tracking under senior guidance.

Design, develop, and test embedded C++ software for automotive infotainment and digital displays. Lead system-level architecture and multi-display integration, build reusable UI rendering frameworks, optimize real-time performance (memory/CPU/log analysis), and collaborate cross-functionally while applying Agile practices and continuous integration/testing.

Design and implement scalable zero trust and secure access architectures across complex hybrid networks. Conduct deep analysis of network access paths, author reusable reference architectures, implement mesh VPN and identity-aware proxy solutions, automate deployments with IaC and CI/CD, collaborate cross-functionally, drive governance and metrics, mentor engineers, and participate in incident response and remediation.