Level

Amazon

Sr. Software Development Engineer, ML Infrastructure Team

Amazon is hiring a Sr. Software Development Engineer, ML Infrastructure Team in Cupertino, United States. It pays $193k-$262k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

  • Little AI ●○○○ is how Level rates this software engineer role: aI is not part of the work.
  • The listed pay starts 16% above the typical software engineer posting on Level.
  • Tools and skills the posting cites include AI automation.
  • Level lists 21,000+ other open roles at Amazon.
  • The role was posted in the last few days.

AI in this role

ai-automation
Want to help drive the success of Machine Learning technologies at AWS? Do you have the skills and motivation to own the infrastructure that enables peer teams to ship high-quality ML networking software? We want to talk to you!

We seek a Senior Software Development Engineer for the Machine Learning (ML) Infrastructure team to own and evolve the platforms used to guarantee top performance of AWS ML and High Performance Computing (HPC) technologies developed by our organization. Our performance data directly influences launch decisions for new EC2 instance types and has visibility at the highest levels of the company. Bring your exceptional knowledge of CI/CD automation, cluster management, and ML/HPC workloads to bear on the cutting-edge software we develop. Join us as we expand the AWS offerings for AI, including Trainium, Neuron and the Elastic Fabric Adapter (EFA).

Key job responsibilities
Own the infrastructure that monitors and reports on functionality and performance of massive testing workloads run at scale across multiple GPU instance types. 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. 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. 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. 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. Drive cross-team readiness for new instance type launches by delivering the performance data that shapes go/no-go decisions. Manage GPU compute capacity planning and provisioning across the organization. Own the complexity of infrastructure that covers many instance types, software stacks, Linux operating systems, and cutting-edge releases — and make it easy to evolve.

A day in the life
You write Python to orchestrate test workloads across large GPU clusters and TypeScript with CDK to ensure all infrastructure is code, reviewed and committed to automated pipelines. You manage shared development clusters using SLURM and AWS ParallelCluster, supporting multiple teams of developers while keeping costs down. You build AI-powered automation that analyzes nightly test results and surfaces actionable insights to developers. You write crisp designs for your projects, drive cross-team alignment, and make architectural decisions that affect how the organization tests and releases software.

About the team
We are part of Annapurna Labs, a subsidiary in AWS that builds software and hardware that make ML on EC2 work. Our organization is a dedicated group of innovators that have invented new networks, new silicon, new software suites, and combined those to entice customers to move immense ML and HPC workloads to the cloud. The ML Infrastructure team is laser focused on making AWS the best and most cost-effective place for customers to do AI at scale. Our work directly enables the launch of new GPU instance types — the performance data we produce reaches senior leadership and shapes strategic decisions.

Basic qualifications

- 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

Preferred qualifications

- Bachelor's degree in computer science or equivalent

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; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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

How we rate this

Sr. Software Development Engineer, ML Infrastructure Team at Amazon rates 25 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

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Pay

This job starts at
$193k
Typical software engineer job
$167k

This posting starts 16% above the typical software engineer job. See software engineer jobs

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