Sr. Software Development Engineer- ML Engineer, Frontier AI Robotics

Job Description

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.

Requirements

• 5+ years of non-internship professional software development experience
• 5+ years of programming with at least one software programming language experience
• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience as a mentor, tech lead or leading an engineering team
• 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
• Deep understanding of LLM algorithm and deep learning framework like PyTorch
• Mathematics and Statistics: Strong understanding of linear algebra, calculus, probability, and statistics

Responsibilities

• Building and optimizing distributed training infrastructure for large-scale machine learning models
• Working closely with scientists and engineers to deliver scalable, high-performance systems
• Powering state-of-the-art AI research and applications
• Developing sophisticated perception systems and creating adaptive manipulation strategies
• Leveraging Amazon's computational infrastructure and real-world datasets for training and deploying models
• Collaborating with cross-functional teams to integrate new models and features

Benefits

• Medical, dental, and vision coverage (multiple plan options)
• Health savings and flexible spending accounts
• 24/7 Employee Assistance Program for mental health support
• 401(k) with company match and various investment choices
• Company-paid life/AD&D and disability insurance
• Restricted stock units (RSUs) for employee ownership
• Child care and elder care referrals, adoption assistance
• Paid maternity and parental leave (including Ramp Back)
• Paid time off (PTO) and company holidays
• Employee discount on Amazon.com products
• Career Choice program (95% tuition and textbook coverage)