Staff ML Infrastructure Engineer - Embodied AI Offboard Perception

At General Motors, our product teams are redefining mobility by creating vehicles and experiences that are designed not just to be seen but to be felt. Through a human‑centered design process, we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale. What You’ll Do Design, build, and maintain machine‑learning infrastructure that enables rapid development, training, evaluation, and deployment of offboard perception models. Own the integration of models into production systems, including packaging, validation, deployment, and rollout strategies. Implement CI/CD pipelines for ML systems, including automated testing, model validation, performance‑regression checks, and deployment automation. Establish model evaluation and observability frameworks, including training metrics, inference performance metrics, data‑quality checks, and production‑monitoring dashboards. Develop infrastructure for experiment tracking and benchmarking, enabling teams to compare model architectures, datasets, hyperparameters, and training procedures in a reliable and repeatable way. Support efficient dataset curation and ingestion pipelines that help prioritize high‑value data, accelerate iteration cycles, and improve model performance on hard‑edge cases. Partner with ML engineers, researchers, and software teams to ensure models can be reliably integrated into larger autonomy stacks and production services at scale. Define and enforce best practices for ML systems engineering, including reproducibility, configuration management, artifact management, security, and operational readiness. Support technical collaboration through code reviews, design reviews, and mentorship, helping raise the quality and maintainability of ML infrastructure across the organization. Skills & Abilities Strong software‑engineering fundamentals and experience building reliable, maintainable, and scalable production systems. Proficiency in Python and experience using ML and scientific‑computing libraries such as PyTorch, NumPy, and related tooling. Experience building and supporting ML training and deployment pipelines, including data processing, experiment execution, model packaging, and production rollout. Experience deploying ML models into production environments, with understanding of end‑to‑end workflows such as validation, serving, monitoring, and lifecycle management. Familiarity with distributed training and large‑scale compute infrastructure, including GPUs, cluster scheduling, and performance optimization for training workloads. Experience with containerization, orchestration, and automation tools such as Docker, Kubernetes, workflow schedulers, and CI/CD systems. Experience with model observability and operational metrics, including training metrics, inference performance, reliability monitoring, and data/model drift detection. Strong communication and collaboration skills, with the ability to work effectively across ML, software, data, and systems engineering teams. Experience in robotics, perception systems, or autonomous driving is preferred. Remote/Hybrid This role is based remotely. If you live within a 50‑mile radius of Austin, Detroit, Warren, Milford, or Mountain View, you are expected to report to that location three times per week, at minimum. Compensation The salary range for this role is $189,300.00 to $290,700.00. Bonus potential is available through an incentive pay program that offers payouts based on company performance, job level, and individual performance. Benefits Medical, dental, and vision coverage. Health Savings Account and Flexible Spending Accounts. Retirement savings plan. Sickness and accident benefits. Life insurance. Paid vacation and holidays. Tuition assistance programs. Employee assistance program. GM vehicle discounts. Company vehicle evaluation program for eligible employees who complete a motor‑vehicle‑report review. Relocation benefits (if eligible). Legal EEO Statement General Motors is committed to being a workplace that is not only free of unlawful discrimination but also genuinely fosters inclusion and belonging. All employment decisions are made on a non‑discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, veteran status, or any other similarly protected status in accordance with federal, state, and local laws. #J-18808-Ljbffr