Engineering interviews at Nebius

Our interviews are built by the engineers you’d actually work with. Find out what to expect below.

The interview process

Apply

We review your background relative to the role and respond within three business days.

Meet your recruiter

A 30-minute conversation about the role, your background and your expectations. Ask us any questions –– we’re here to help!

Show us how you think

Multiple focused technical rounds. Details for each track are below.

Build with us

We’ll be in touch with our decision. If it’s good news, you’ll chat with your recruiter and team lead about next steps.

Interview rounds by role

Site Reliability Engineer

Typically 5 interview stages (up to 6 for senior or specialist roles).

You’ll start with a technical screening on Linux, networking, Kubernetes, and core DevOps concepts, plus a practical coding exercise.

Next is a hands-on troubleshooting interview focused on Kubernetes and infrastructure debugging, followed by a deeper technical assessment.

Senior candidates, or those with highly specialized expertise, may complete an additional systems architecture or specialist interview.

The final stage is a Technical Deep Dive into your experience, followed by introductions to the teams you may join and discussions with the hiring managers.

Engineering Bootcamp

Find the right team, not just the right job.

Choosing the right team is just as important as choosing the right company. That’s why many engineers on our core cloud team start with Engineering Bootcamp, a 12-month rotational program designed to help you discover where you’ll have the biggest impact.

How it works

Rotate across up to four engineering teams during your probation period
Contribute to real production projects and meaningful engineering tasks from day one
Work alongside experienced engineers and see how different teams operate
Get regular feedback throughout to support your growth

Why engineers love it

Find your best fit: experience multiple teams before choosing the team where your skills, interests and ambitions align.
Work on real projects: contribute to production systems from the very beginning.
Accelerate your org knowledge: build knowledge across our engineering organization and work with engineers across different products and infrastructure early on.

Think out loud. We care more about your thinking than a perfect answer. Walk us through your assumptions, the trade-offs you’re weighing, and why you’d choose one approach over another. Be ready to adapt if the problem changes and offer alternative solutions whenever possible, even if we’ve moved on.

Engineering fundamentals: strong algorithms, data structures, and systems thinking for your specialization. Practice on LeetCode or HackerRank, and brush up on Numbers Every Programmer Should Know, measuring algorithm complexity, tree traversals, working with stacks/queues/cycles, and asynchrony. SREs should also sharpen Linux and scripting skills. Check code for errors and readability before submitting.

Practical experience. Be ready to go deep on things you’ve actually built, debugged, and shipped, including what didn’t work and why. The decisions matter as much as the outcomes.

Collaborate with your interviewer. Don’t hesitate to ask for a hint. Interviewers are there to guide you through problems, not just score the result.

Ready to build?

Explore our open roles, learn more about the teams and their work, and find your next challenge at Nebius.

Apply now

FAQ

One of the final stages of our interview process is a 90-minute Technical Deep Dive about one significant project you’ve worked on. Rather than asking hypothetical questions, we want to understand what you actually built, the decisions you made, and the impact you had.

Pick your project
Choose a project where you were a key contributor and can clearly explain both the technical and business context in depth. Ideally it’s day-to-day work rather than a side project, and one that shows real scale and complexity.

It could be a product or feature you launched, a large infrastructure or platform change, a migration or modernization project, a performance or scalability improvement, an ML system or any project you’re particularly proud of.

What we’ll cover
We’ll go deep on this one project rather than wide across several, covering things like the problem you were solving, your role, the key trade-offs and decisions, the biggest technical challenges, how the solution was deployed and operated, and the results.

We’re most interested in your individual contribution, rather than the team’s overall achievement.

Be prepared to explain why you made particular decisions, what alternatives you considered, and what you learned along the way. It’s perfectly fine to reflect on decisions you would make differently today as we value thoughtful engineering and continuous learning.

What we’re listening for

Engineering judgement: how you approach complex problems and make technical decisions

Technical depth: the most technically challenging aspects of your project

Collaboration: how you worked with others to get it done

Production experience: Many of our teams build and operate large-scale cloud infrastructure, so we’re interested in your experience running software in production at scale.

While cracking algorithmic tasks doesn’t always equate to being a successful software engineer, we’ve found that they can be a useful indicator of structured problem-solving, technical fluency and the ability to work through complex engineering challenges.

Knowledge of algorithms can come in handy, especially when designing high-performance systems. A system might not start as high-load, but it’s important to establish some early groundwork that will allow it to handle a significant load when needed. A strong understanding of algorithms can play an important role in making those design decisions.

To ensure a fair and consistent evaluation process, candidates are expected to complete all interviews and assessments using their own knowledge and independent problem-solving. The use of AI tools (e.g., ChatGPT, Copilot, etc.), answer-generating services, or other external assistance to generate or guide responses is not permitted unless explicitly stated otherwise.

This expectation applies to all stages of the interview process, including phone screens, virtual or in-person interviews, and technical or take-home assessments. Candidates may be asked to explain their thinking, walk through their approach, or reproduce their work as part of the evaluation.

Failure to adhere to these guidelines may result in removal from the interview process.