Note: The job is a remote job and is open to candidates in USA. General Motors is redefining mobility through innovative vehicle and experience design. They are seeking a Staff ML Infrastructure Engineer to develop and deploy machine learning solutions for autonomous vehicle behavior, collaborating closely with cross-functional teams to shape technical direction and support engineers' growth.
Responsibilities
- Design, build, and maintain ML 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, 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
- Strong software engineering fundamentals, including experience building reliable, maintainable, and scalable production systems
- Proficiency in Python, with 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
Benefits
- Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
- GM offers a variety of health and wellbeing benefit programs.
- Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.
- This job may be eligible for relocation benefits.
- Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.
Company Overview
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