In this role, you will be responsible for the development, enablement, and performance optimization of large scale ML model training across diverse model families. This includes massive scale pre-training and post-training of LLMs with Dense and Mixture-of-Experts architectures, Multimodal models that are transformer and diffusion based, and Reinforcement Learning workloads. You will work at the intersection of ML research and high performance systems, collaborating closely with chip architects, compiler engineers, runtime engineers and AWS solution architects to deliver cost-effective, performant machine learning solutions on AWS Trainium based systems.
Key job responsibilities
You will design, implement and optimize distributed training solutions for large scale ML models running on Trainium instances. A significant part of your work will involve extending and optimizing popular distributed training frameworks including FSDP (Fully-Sharded Data Parallel), torchtitan and Hugging Face libraries for the Neuron ecosystem.
A core focus of this role involves developing and optimizing mixed-precision and low-precision training techniques. You will work with BF16, FP8, and emerging numerical formats to maximize training throughput while maintaining model accuracy and convergence quality. This requires implementing precision aware training strategies, loss scaling techniques, and careful gradient management to ensure training stability across reduced precision formats. Understanding the tradeoffs between computational efficiency and numerical fidelity is essential to success in this position.
Beyond precision optimization, you will profile, analyze, and tune end-to-end training pipelines to achieve optimal performance on Trainium hardware. You will partner with hardware, compiler, and runtime teams to influence system design and unlock new capabilities. Additionally, you will work directly with AWS solution architects and customers to deploy and optimize training workloads at scale.
BASIC QUALIFICATIONS
- Bachelor's degree in computer science or equivalent
- 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
- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience as a mentor, tech lead or leading an engineering team
- Experience in machine learning, large scale training with LLMs and expertise in Pytorch.
PREFERRED QUALIFICATIONS
- Master's degree in computer science or equivalent
- Experience in computer architecture
- Previous software engineering expertise with Pytorch/Jax/Tensorflow, Distributed libraries and Frameworks, End-to-end Model Training.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, CA, Cupertino - 193,300.00 - 261,500.00 USD annually
