דרושים » סטודנטים » רכז /ת תפעול ובקרה סולארית

We are looking for a Software Development Student to join us part-time alongside your studies. You will work on real firmware that ships on production ML servers, writing and testing code, debugging on real hardware, and learning how large-scale accelerator platforms are built from the ground up. You will be working closely with silicon, 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 firmware components 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 and automation that improve the team's development and validation flow.
- Collaborate with firmware, hardware, and platform engineers across the group.

For our Cyber Security solutions and attack mitigation business, we invite you to join the DP QA department responsible for high‑end enterprise security solutions. Our cutting‑edge security platforms simplify operations while ensuring resilience, efficiency, and SLA adherence.

In this role, you will take an active part in mastering our Next‑Generation Cyber Security products, with a strong emphasis on automation, quality engineering, and the adoption of AI‑driven testing methodologies.

You will work in an Agile Scrum environment within a dynamic, fast‑growing, and highly innovative team.

What will you do?
Planning, design, development, reporting, and analysis of manual and automation tests.
End‑to‑end testing of various DP features and components.
Building and maintaining automation frameworks for complex networking and security environments.
Utilizing AI‑powered tools to improve test coverage, defect detection, and root‑cause analysis.
Developing test insights using AI/ML models for anomaly detection and optimization of regression cycles.
Collaborating with development, QA, and data teams to integrate AI‑assisted automation into CI/CD pipelines.
Participating in Agile processes, contributing to test strategy and continuous quality improvement.