AmazonEFA Network Software Engineer I, Annapurna Labs
Amazon is hiring an EFA Network Software Engineer I, Annapurna Labs in Seattle, United States. It pays $111k-$160k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- On Level's scale, this software engineer role is Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include C, Git and Open Mpi.
- Level classifies it as a junior role.
- Level lists 20,000+ other open roles at Amazon.
AI in this role
Write high-performance C software for networking infrastructure supporting machine learning and high-performance computing clusters.
We own the user-space software that makes the Elastic Fabric Adapter (EFA) network card work for Machine Learning (ML) and High-Performance Computing (HPC) customers on AWS. Across multiple projects written in C, our team enables customers to network thousands of GPU and CPU instance types to handle the toughest clustered workloads. Be a part of a dynamic, fast-paced group that has a big impact every day on the hottest companies doing AI and HPC today.
Key job responsibilities
You will write the highest-performing code in C for multiple open source projects supporting EFA, such as Libfabric and Open MPI. You will work with multiple teams in the stack to invent new APIs for the latest concepts in networking in the cloud. Dive deep into how your customers are doing collectives and messaging at high bandwidth and low latency. Provide expert-level support to some of the biggest names in AI in the world.
A day in the life
Start from the needs of your customer and invent new ways of cutting the occupancy of the software stack for EFA. Get your peers and stakeholders on board with excellent written designs. Write comprehensive tests to drive the development of new features and guard against regressions. Work with our ML Infrastructure team to see your products perform on 100s and 1000s of top-end machine clusters.
About the team
We are a fast-paced team that owns the user-space software stack for EFA. As part of Annapurna Labs in AWS we are very nimble, paying careful attention to what the AI industry is going to try next, and having our products ready. We focus heavily on automation, confining operations to the most interesting problems as customers continuously experiment with what our network can do. Our team is a place of growth, concentrating on your career and goals and motivating you to achieve your highest potential.
Basic qualifications
- Bachelor's degree or above in computer science, computer engineering, or related field, or Bachelor's degree
- Strong programming skills in C (coursework, projects, or internship experience)
- Familiarity with systems programming concepts (memory management, performance optimization, Linux)
- Experience with source control (Git), code reviews, and build processes (internship experience counts)
Preferred qualifications
- Contributions to open source projects (Libfabric, Open MPI, or similar)
- Coursework or experience in computer networking (protocols, latency optimization, distributed systems)
- Experience writing performance-critical code with a focus on minimizing instruction count and occupancy
- Familiarity with HPC or ML infrastructure concepts
- Experience with the full software development lifecycle including testing and operations
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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, WA, Seattle - 110,500.00 - 160,000.00 USD annually
How we rate this
EFA Network Software Engineer I, Annapurna Labs at Amazon rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ 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
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- This job starts at
- $111k
- Typical software engineer job
- $167k
This posting starts 34% below the typical software engineer job. See software engineer jobs
Questions you could be asked
- Tell me about a project where systems programming was part of your work. What did you do?
- Tell me about a project where performance optimization was part of your work. What did you do?
- Tell me about a project where networking was part of your work. What did you do?
- Tell me about a project where linux was part of your work. What did you do?
- Walk me through how you've used C in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Systems Programming, Performance Optimization, Networking, Linux, and C. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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