Software Development Student, Software Development Student, Machine Learning Israel (MLIL) FLOW

Description

Annapurna Labs builds the custom silicon that powers Amazon's machine learning accelerators. Our Machine Learning Israel (MLIL) FLOW team in Tel Aviv builds the software that takes these ML servers from the manufacturing line into the fleet — from manufacturing and provisioning test flows to hardware vetting, fleet health monitoring, and performance benchmarking across the platform.

We are looking for a Software Development Student to join us part-time alongside your studies. You will work on real automation and test infrastructure that runs on production ML servers, writing and testing code, debugging on real hardware, and learning how large-scale accelerator platforms are validated and brought into the fleet. You will be working closely with firmware, hardware, and cloud teams to bring new accelerator platforms from first power-on to production. You will be paired with experienced engineers who will mentor you, review your code, and help you grow.

This is a hands-on role for a student who is curious about how hardware and software meet, enjoys solving problems at a low level, and wants to make a real impact on systems used at massive scale.

Key job responsibilities
- Develop, test, and debug automation and test flows for ML accelerator servers
- Write clean, well-tested code and participate in code reviews
- Investigate and root-cause issues on real hardware in the lab
- Build tools, dashboards, and automation that improve the team's development and validation flow
- Collaborate with firmware, hardware, and platform engineers across the group

A day in the life
You'll start by reviewing overnight CI results and helping triage failures — learning to distinguish between vendor regressions, firmware issues, and ML stack bugs. You might then work on extending a test framework so hardware engineers can validate a new component with minimal friction. After lunch you could be writing Python scripts that benchmark inference latency, or building a Grafana dashboard that tracks regression trends across builds. Throughout the day you'll collaborate with senior engineers across firmware, data-plane, and ML teams — and use AI-assisted tools to move faster.

Basic Qualifications

- - Currently enrolled in a Bachelor's or higher degree in Computer Science, Computer/Electrical Engineering, or a related field
- - At least 3 full semesters remaining until graduation
- - Available to work part-time (at least 2-3 days per week) alongside studies
- - Strong problem-solving skills and eagerness to learn in a hardware-focused environment
- - Team player, highly motivated, passionate about SW development, and a fast self-learner

Preferred Qualifications

- - Programming experience in Python (C / C++ a plus)
- - Experience with Linux, scripting, automation, or test frameworks
- - Exposure to hardware debugging, communication protocols (I2C, PCIe, SPI), or data pipelines and monitoring/dashboards
- - Demonstrated early adopter of AI-assisted development tools — uses LLMs or code-generation agents as part of daily workflow

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