Amazon.com, Inc.-posted 27 days ago
Full-time • Mid Level
San Francisco, CA
5,001-10,000 employees
General Merchandise Retailers

We are seeking a highly skilled Machine Learning Systems Engineer to join Frontier AI Robotics team. This role focuses on building and optimizing distributed training infrastructure for large-scale machine learning models, particularly in deep learning and transformer-based architectures. You will work closely with scientists and engineers to deliver scalable, high-performance systems that power state-of-the-art AI research and applications. About the team At Frontier AI & Robotics, we're not just advancing robotics - we're reimagining it from the ground up. Our team is building the future of intelligent robotics through frontier foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence - from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.

  • Design, build, and optimize machine learning infrastructure for large-scale training and inference.
  • Apply PyTorch, Python, and C++ skills to engineer modular, scalable ML systems.
  • Evaluate and implement parallelism techniques such as data, tensor, model, and pipeline parallelism.
  • Monitor and optimize GPU memory and throughput for training large models efficiently.
  • Collaborate cross-functionally with research, data infra teams to integrate new models and features.
  • 3+ years of non-internship professional software development experience
  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience programming with at least one software programming language
  • Deep understanding of LLM algorithm and deep learning framework like PyTorch.
  • Mathematics and Statistics: Strong understanding of linear algebra, calculus, probability, and statistics.
  • 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Bachelor's degree in computer science or equivalent
  • Our compensation reflects the cost of labor across several US geographic markets.
  • The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/year in our highest geographic market.
  • Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience.
  • Amazon is a total compensation company.
  • Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
  • For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits.
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