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Job Description

Build integrations that help customers run distributed training and inference on AWS Neuron at scale. Onsite in Cupertino, CA, the Neuron Containers team at Annapurna Labs (U.S.) Inc. is hiring a Software Development Engineer to own Neuron integration across Kubernetes, ECS, and Slurm. You will also deliver Neuron Deep Learning Containers (DLCs) and Deep Learning AMIs (DLAMIs), supporting deployment across EKS, ECS, EC2, and SageMaker.

What you’ll work on

In this role, you will design and implement container platform integrations that manage ML accelerator resources, including device plugins, DRA drivers, and operators. You will build and maintain Neuron DLCs and DLAMIs so customers can deploy workloads across common AWS compute and orchestration environments, including EKS, ECS, EC2, and SageMaker.

As adoption grows, you will diagnose and resolve performance and scalability issues in large customer clusters. You will also streamline delivery by deprecating legacy software and reducing complexity in container delivery pipelines. The scope includes end-to-end engineering across the development lifecycle, from design documentation and implementation to testing, deployment, and operations.

How you’ll contribute day to day

  • Collaborate with teams across the Neuron organization and with customers to build and maintain integrations for current and next-generation accelerators.
  • Participate in architecture reviews, triage test failures, resolve operational issues, and contribute upstream to Kubernetes projects.
  • Debug platform integration problems across how Neuron interacts with container runtimes, orchestrators, and scheduling systems at scale.

Required qualifications

  • 3+ years of non-internship professional software development experience.
  • 2+ years of non-internship design or architecture experience, including experience with design patterns and reliability and scaling for new and existing systems.
  • Experience programming with at least one software programming language.
  • 3+ years of full software development life cycle experience, including coding standards, code reviews, source control management, build processes, testing, and operations.
  • Bachelor’s degree in computer science or equivalent.
  • Experience with distributed systems or large-scale cluster infrastructure.
  • Familiarity with ML training/inference workflows (distributed training, collective).
  • Experience with AWS compute services (EC2, EKS, ECS, ECR).
  • Hands-on experience with Helm, Prometheus, or Kubernetes operator frameworks.
  • Experience with container image pipelines, Deep Learning Containers, or Deep Learning AMIs.
  • Contributions to open-source projects, particularly in the Kubernetes ecosystem.

Relevant technologies

  • Kubernetes, ECS, Slurm, EKS, EC2, SageMaker
  • Helm, Prometheus, Kubernetes operator frameworks
  • ECR, container image pipelines
  • Neuron Deep Learning Containers (DLCs), Deep Learning AMIs (DLAMIs)
  • Device plugins, DRA drivers, operators
  • Distributed systems

Benefits

  • Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance, 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
  • Parental leave

Salary range

USD 165,200 - 223,600 per year

Los Angeles County applicants

Job duties include working safely and cooperatively, adhering to standards of excellence despite stressful conditions, communicating effectively and respectfully to ensure exceptional customer service, following federal, state, and local laws and Company policies, and maintaining judgment, stress management, trustworthiness, professionalism, and safeguarding business operations and the Company’s reputation. Criminal history may have a direct, adverse, and negative relationship with some material duties. Pursuant to the Los Angeles County Fair Chance Ordinance, qualified applicants with arrest and conviction records will be considered.

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