Senior Software Development Engineer, Machine Learning Israel (MLIL) — Integration Validation

Amazon is hiring a Senior Software Development Engineer, Machine Learning Israel (MLIL) — Integration Validation in Tel Aviv, Israel. Level rates it ; you can apply on Level.

AI in this role

Lead the design and delivery of systems software, CI/CD pipelines, and validation infrastructure for next-generation ML inference accelerators.

vllmci-cdnkinixlkiro

systems-softwaremachine-learningtesting-frameworksperformance-benchmarkingpython

Annapurna Labs designs silicon and software that accelerates innovation. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.
The Integration team is looking for a Senior Software Development Engineer to lead the design and delivery of systems software for our next-generation ML accelerator servers. In this role you will own the design and implementation of CI/CD pipelines, test frameworks, and system-level validation for our next-generation ML inference accelerator platform. You will work across the full stack — from firmware interfaces through data-plane performance benchmarking to production fleet readiness — ensuring every component is validated end-to-end before it reaches customers.
This is a greenfield environment with rapidly growing scope: new silicon, new software stacks (vLLM, NKI, NIXL), and new fleet-scale challenges. We are looking for a senior IC who can independently drive technical decisions, scale our validation infrastructure, and raise the bar on engineering quality across the group.

Key job responsibilities
Own and evolve CI/CD pipelines — from pre-merge gates through continuous deployment to fleet.
Design and implement test frameworks that enable firmware and data-plane developers to write, run, and maintain tests with minimal friction.
Architect system-level test suites that stress control-plane and data-plane components beyond provisioning and vetting flows.
Build and maintain performance benchmarking infrastructure for LLM inference workloads (Prefill + Decode), including dashboarding and regression detection.
Drive integration of third-party vendor code (nightly drops) into CI/CD, ensuring quality gates catch regressions early.
Participate in feature design reviews, contributing test plans and challenging coverage gaps.
Define and own Continuous Testing in production environments (CTS).
Leverage AI-assisted development tools (Kiro, LLM-based code generation) to accelerate team velocity and pioneer new engineering workflows.

A day in the life
You'll start your day reviewing CI pipeline results from overnight runs, triaging failures to determine whether a regression came from a vendor code drop, a firmware change, or an ML serving stack update. Mid-morning you might pair with a hardware engineer to design test cases for a new bus-level reset flow, then pivot to extending the performance benchmarking framework to catch a latency regression. After lunch you'll join a feature design review — challenging test coverage gaps and deciding where system-level validation needs to live. The rest of your afternoon could be spent writing a new pipeline stage that gates deployment on accuracy checks, or building a dashboard that gives the group visibility into fleet-readiness metrics. Throughout the day you'll lean on AI-assisted development tools to accelerate everything from infrastructure code to root-cause analysis.

Basic qualifications

- Experience leading the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
- Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design
- 7+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent

Preferred qualifications

- Knowledge of Python and/or C++ programming
- Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware
- Experience in DevOps, CI/CD, pipeline, jenkins or other equivalents
- Experience with elastic, grafana, cloudwatch, or other equivalents

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.

How we rate this

Senior Software Development Engineer, Machine Learning Israel (MLIL) — Integration Validation at Amazon rates 70 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● 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. Open the description and count.

Key facts

Senior Software Development Engineer, Machine Learning Israel (MLIL) — Integration Validation is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in IL, Tel Aviv.
The job was posted on October 4, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Systems SoftwareMachine learningTesting FrameworksPerformance BenchmarkingPythonvLLMCi CdNki

Questions you could be asked

Tell me about a project where systems software was part of your work. What did you do?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where testing frameworks was part of your work. What did you do?
Tell me about a project where performance benchmarking was part of your work. What did you do?
Tell me about a project where python was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Systems Software, Machine learning, Testing Frameworks, Performance Benchmarking, and Python. 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.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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