Staff ML Infrastructure Engineer

🔥 0 minutes ago

🏄 California – Remote

🏄 California – Remote

💵 $189.3k - $290.7k / year

⏰ Full Time

🔴 Lead

👷 Infrastructure Engineer

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General Motors

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1908

🚗 Transport

⚡ Energy

🏢 Enterprise

💰 $500M Grant on 2024-07

Transport • Energy • Enterprise

General Motors is a leading multinational corporation in the automotive industry, committed to creating a future with zero crashes, zero emissions, and zero congestion. With operations and facilities worldwide, GM focuses on innovation across various areas including engineering, manufacturing, and information technology. The company emphasizes diversity, inclusion, and the development of sustainable technologies to shape the future of mobility.

📋 Description

• Lead the design, implementation, and deployment of scalable platforms and tools that drive machine learning model training and evaluation workflows across GM. • Own complex technical projects end-to-end, making key architectural decisions and technical trade-offs. • You will be a core contributor to team planning, design reviews, and code quality. • Take a holistic view of projects, considering their impact across multiple teams, and across a longer timeline. • Proactively drive technical prioritization. • Collaborate closely with partner teams to ensure maximum benefit from the systems we build. • Help shape our team through technical interviewing with high, well-calibrated standards, and play an essential role in recruiting. • Mentor and onboard junior engineers and interns, helping them grow their careers.

🎯 Requirements

• 5+ years of experience building large-scale distributed systems, applications, or advanced ML systems • Proven track record of designing robust frameworks with high-quality, durable APIs • Deep understanding of machine learning algorithms with hands-on application • Expertise in building reliable, high-performance, and cost-efficient systems on modern cloud infrastructure • End-to-end experience across the ML development lifecycle, including MLOps practices • Strong cross functional collaboration skills across teams and organizations • Exceptional coding skills in Python or C++ • Strong interest in autonomous driving and its transformative potential • BS, MS, or PhD in Computer Science, Mathematics, or equivalent practical experience. • Nice to have: Experience with distributed training methodologies • Experience scaling ML training across large GPU/CPU clusters or other accelerators • Familiarity with deep learning frameworks (e.g., PyTorch, TensorFlow) • Experience with performance profiling and state-of-the-art training optimization techniques, including their impact on model performance • Experience with advanced build systems (e.g., Bazel, Buck, Blaze, CMake) • Proficiency with containerization and orchestration technologies (e.g., Docker, Kubernetes)

🏖️ Benefits

• 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.