The Annapurna Labs team at Amazon Web Services (AWS) builds AWS Neuron, the software development kit used to accelerate deep learning and GenAI workloads on AWS Trainium, Amazon's custom machine learning accelerator. Neuron includes an ML compiler, runtime, collectives library, and application framework that integrate with PyTorch and JAX, so customers can train frontier-scale models on Trainium without rewriting their stack.
The Distributed Training team enables the training of a wide range of models, from large-scale pretraining through post-training and reinforcement learning, on AWS's custom ML accelerators. As more customer workloads shift toward RLHF, PPO/GRPO, and other fine-tuning methods, we are building the distributed training infrastructure, parallelism techniques, numerics, and high-performance kernels that these methods depend on. As part of the broader Neuron organization, we work across frameworks, kernels, compiler, runtime, and collectives - a true hardware and software co-design in practice. We not only optimize current performance but also contribute to future architecture designs, since the gaps we characterize today become requirements for the next generation of Trainium.
We are looking for software engineers to help build and fine tune these distributed training solutions. This role offers a rare opportunity to work at the intersection of machine learning, high-performance computing, and distributed systems, where you will help shape the direction of AI acceleration technology.
Key job responsibilities
You'll implement and tune components of our distributed training stack for large-scale training, post-training, and reinforcement learning workloads on the latest Trainium instances, working across PyTorch and the Neuron software stack. You'll contribute to parallelism strategies such as data, tensor, and pipeline parallelism and apply reduced-precision formats under the guidance of senior team members. You'll profile workloads to help determine whether a bottleneck sits in compute, memory, collectives, or host overhead, and work with compiler, runtime, and collectives engineers to help land the fix. You'll build and maintain internal tooling, benchmarks, and tests that keep the team's performance work reproducible, and take on increasing ownership as you grow in the role.
BASIC QUALIFICATIONS
- Bachelor's degree or above in computer science or equivalent
- 3+ years of experience with full software development life cycle in production
- 3+ years of experience with at least one programming language such as Python, C/C++, or a similar language
- 2+ years of experience with system design (design patterns, reliability and scaling) of new or existing systems
- Familiarity with LLM/transformer fundamentals such as attention mechanisms, autoregressive decoding, KV-cache behavior, and various forms of parallelism
PREFERRED QUALIFICATIONS
- Master's degree or above in computer science or equivalent
- Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware, or experience in computer architecture
- Experience with ML frameworks such as Pytorch/Jax, Distributed libraries and Frameworks, RL frameworks or End-to-end Model Training
- Experience with performance engineering: workload profiling, characterization (compute bound, memory bound, network bound), and optimization
- Experience with open source projects
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 - 165,200.00 - 223,600.00 USD annually
