Sr. Software Development Engineer, ML Infrastructure Team

Amazon Amazon · Big Tech · Cupertino, CA · Software Development

Senior Software Development Engineer on the ML Infrastructure team at AWS, responsible for owning and evolving the platforms that ensure top performance of ML and HPC technologies. This involves building and operating CI/CD systems, orchestrating large GPU clusters, analyzing performance data with LLMs, and managing GPU capacity. The role focuses on the infrastructure supporting ML workloads, directly impacting the launch of new EC2 instance types.

What you'd actually do

  1. Own the infrastructure that monitors and reports on functionality and performance of massive testing workloads run at scale across multiple GPU instance types.
  2. Build and operate CI/CD systems using Jenkins, internal Amazon tools, Linux, and public AWS products to automate the testing and delivery of ML networking libraries — including collective communication frameworks, network transport layers, and GPU communication libraries.
  3. Write Python code that orchestrates large clusters, runs benchmarks and ML applications across a wide matrix of instance types, operating systems, and software stack versions.
  4. Use AWS Managed Grafana and Athena to digest the massive amount of performance data generated by these workloads and build dashboards and alarms that catch functional and performance regressions before they reach customers.
  5. Build intelligent automation using LLMs to analyze test failures, perform root cause analysis, deduplicate regressions, and generate reports — reducing manual toil and accelerating issue resolution.

Skills

Required

  • 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
  • 5+ years of non-internship professional software development experience
  • 5+ years of programming with at least one software programming language experience
  • Experience coding in Python, TypeScript, CDK

Nice to have

  • Experience with HPC job schedulers (SLURM), Jenkins, or GPU compute infrastructure
  • Experience with AWS infrastructure services (EC2, CDK, CloudFormation, Step Functions)
  • Familiarity with ML/HPC networking or collective communication libraries (NCCL, MPI, libfabric)
  • Experience building automation or tooling using large language models (LLMs)

What the JD emphasized

  • own the infrastructure
  • own and evolve the platforms
  • own the complexity of infrastructure

Other signals

  • ML infrastructure
  • performance of AWS ML and High Performance Computing (HPC) technologies
  • CI/CD automation
  • cluster management
  • ML/HPC workloads
  • Trainium, Neuron and the Elastic Fabric Adapter (EFA)
  • GPU instance types
  • AWS Managed Grafana and Athena
  • LLMs to analyze test failures
  • GPU compute capacity planning and provisioning