Staff Machine Learning Engineer

About The Company General Motors (GM) is a leading global automotive manufacturer committed to innovation, sustainability, and safety. With a vision centered around Zero Crashes, Zero Emissions, and Zero Congestion, GM strives to develop advanced mobility solutions that enhance the driving experience while reducing environmental impact. The company fosters a culture of technological excellence, inclusivity, and continuous improvement, empowering its diverse team of engineers, scientists, and industry professionals to shape the future of transportation. Headquartered in Detroit, Michigan, GM operates across multiple locations worldwide, including remote options, and is dedicated to making a positive impact through cutting-edge research, sustainable practices, and customer-centric innovations. About The Role We are seeking a highly skilled and impact-driven Staff Machine Learning (ML) Engineer specializing in ML Training Infrastructure. This role requires a technically proficient leader capable of guiding complex projects through hands-on involvement and strategic oversight. As a key member of our team, you will define the technical direction, design, and development of scalable, reliable, high-performance AI/ML platform infrastructure that supports large-scale model training and research. Your expertise will enable the advancement of autonomous driving technologies and other innovative solutions at GM. You will collaborate closely with machine learning engineers, research scientists, and platform teams across the organization to influence architecture, set engineering standards, and drive the adoption of best practices. This remote/hybrid position offers the opportunity to work from various locations including Sunnyvale, Mountain View, Austin, and Washington, with occasional travel to the main office as needed. Qualifications Bachelor's degree or higher in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience.7+ years of professional software engineering experience.5+ years of specialized experience in AI/ML infrastructure, including distributed training for large-scale models.Proficiency in Python programming, with deep expertise in frameworks such as PyTorch (preferred), TensorFlow, or similar ML systems.Experience designing and operating distributed systems for ML training, including distributed computing, GPU acceleration, and cloud platforms (AWS, GCP, Azure).Proven track record of leading cross-team technical initiatives, delivering impactful results, and influencing platform architecture.Strong architectural judgment and ability to make informed tradeoffs across performance, reliability, usability, and cost.Willingness to travel to Sunnyvale, CA, as required.Ability to operate effectively in highly ambiguous, dynamic environments.Responsibilities Define and lead the architecture, design, and development of scalable ML frameworks and platform capabilities to support model training at scale.Conduct performance analysis and optimization of distributed training workflows to improve scalability, efficiency, and cost-effectiveness across heterogeneous hardware environments.Enhance system observability, debuggability, and operational excellence to ensure robust ML training operations.Own large, ambiguous, cross-functional technical initiatives from strategy to execution, including roadmap development, tradeoff analysis, and delivery.Identify long-term infrastructure investments, set engineering standards, and promote best practices across teams to influence platform evolution.Collaborate with cross-organizational teams to align requirements, resolve technical disagreements, and integrate new capabilities into the ML ecosystem.Mentor engineers through design reviews, technical guidance, and hands-on collaboration to elevate engineering quality and knowledge sharing.Benefits Comprehensive health and wellbeing programs including medical, dental, and vision coverage.Retirement savings plans and flexible spending accounts.Paid vacation, holidays, and sick leave.Tuition assistance and professional development opportunities.Employee assistance programs supporting mental health and work-life balance.GM vehicle discounts and participation in the company vehicle evaluation program.Potential relocation benefits for eligible candidates.Equal Opportunity General Motors is committed to creating a diverse and inclusive workplace. We provide equal employment opportunities to all applicants and employees without regard to sex, race, color, national origin, citizenship, religion, age, disability, pregnancy, sexual orientation, gender identity, veteran status, or any other protected characteristic.