Software Engineer- AI/ML, Amazon Neuron Training

Annapurna Labs (U.S.) Inc.; Cupertino (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Annapurna Labs (U.S.) Inc. at Amazon Web Services (AWS) seeks software engineers to build distributed training components for Neuron on Trainium, integrating with PyTorch and JAX. You will optimize data, tensor, and pipeline parallelism while applying reduced-precision formats under senior guidance.

You will profile workloads to identify bottlenecks, collaborate with compiler/runtime/collectives teams, and contribute to internal tooling, benchmarks, and tests, increasing ownership over time.

Qualifications

• Bachelor's degree or above in computer science or equivalent.
• 2+ years of designing or architecting scalable systems.
• 3+ years of full SDLC experience in production.
• 3+ years of programming in Python, C/C++, or similar.
• Familiarity with LLM/transformer fundamentals like attention and KV-cache.

Responsibilities

• Implement and tune distributed training components for large-scale training on Trainium, across PyTorch and Neuron stack.
• Contribute to parallelism strategies (data, tensor, pipeline) and perform workload profiling.
• Build and maintain internal tooling, benchmarks, and tests to ensure reproducible performance work.
• Take increasing ownership as you grow in the role.

Skills

Systems design & architecture

SDLC in production

Programming: Python/C/C++

LLM/transformer fundamentals

Education

Bachelor's degree or above in Computer Science or equivalent

Master's degree or above in Computer Science or equivalent

Tools

PyTorch / JAX

Distributed libraries & frameworks

RL frameworks

Job description

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.

About the team

Inclusive Team Culture

Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon's culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Work/Life Balance

Our team puts a high value on work-life balance. It isn't about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

Basic Qualifications:

• Bachelor's degree or above in computer science or equivalent
• 2+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience
• 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
• 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

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service