Senior Software Engineer (Data Platform, C++)

About the role

<div class="content-intro"><p><strong>About Nebius:</strong></p> <p>Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.</p> <p>Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.</p> <p>Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&amp;D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&amp;D.</p></div><h4 id="The-role" data-local-id="c41794725a88" data-renderer-start-pos="1">The role</h4> <p data-renderer-start-pos="11" data-local-id="b628b6030a86">We’re looking for a <strong data-renderer-mark="true">Software Engineer with strong C++ expertise</strong> to join the team building and operating <strong data-renderer-mark="true">Nebius Data Platform</strong> — a distributed storage and a processing platform that acts as the company’s “source of truth” and the backbone of many internal (and some external) products.</p> <p data-renderer-start-pos="292" data-local-id="de1e1b789ce4">Nebius Data Platform is a <strong data-renderer-mark="true">single multi-tenant ecosystem based on YTsaurus</strong> — instead of running separate HDFS/Kafka/HBase-style systems, we provide storage, compute, and analytics capabilities inside one platform.</p> <p data-renderer-start-pos="506" data-local-id="bcbb3787b5d5">Built on top of the open-source YTsaurus ecosystem, we run and extend our own Nebius distribution and develop significant in-house functionality (core and platform-level). We can design, implement, and roll out features end-to-end on our clusters without waiting for upstream approvals and contribute upstream when it makes sense.</p> <p data-renderer-start-pos="838" data-local-id="7544511b100f">At scale today, this includes<strong data-renderer-mark="true">~500 servers, ~20k CPU cores</strong> and&nbsp;<strong data-renderer-mark="true">~10 PB of compressed</strong> <strong data-renderer-mark="true">data</strong> in our largest production cluster, supporting workloads ranging from business-critical pipelines and financial transactions to large-scale ML/LLM training datasets and compute.</p> <h4 id="What’s-inside-the-platform" data-local-id="2100fd8e190a" data-renderer-start-pos="1105">What’s inside the platform</h4> <p data-renderer-start-pos="1133" data-local-id="76f8ed17de21">You’ll work on a system that includes (and ties together):</p> <ul> <li data-renderer-start-pos="1195" data-local-id="6ddeb26cab43"><strong data-renderer-mark="true">Distributed Storage (Cypress)</strong>: transactional semantics, tiered storage, erasure coding, replication, and strong reliability expectations.</li> <li data-renderer-start-pos="1336" data-local-id="13562646bfb3"><strong data-renderer-mark="true">Compute &amp; ETL</strong>: a cluster-wide job scheduler (tens of thousands of cores), MapReduce, <strong data-renderer-mark="true">YQL</strong> for SQL-like data processing, and <strong data-renderer-mark="true">SPYT (Spark over YTsaurus)</strong> for modern data engineering.</li> <li data-renderer-start-pos="1518" data-local-id="97897e1cbf8b"><strong data-renderer-mark="true">Interactive analytics (CHYT)</strong>: ClickHouse® instances spun up directly on compute nodes for fast SQL over data in-place.</li> <li data-renderer-start-pos="1640" data-local-id="02d7848ef2e9"><strong data-renderer-mark="true">Dynamic Tables</strong>: low-latency NoSQL KV with distributed ACID transactions for OLTP-style workloads and feature stores.</li> <li data-renderer-start-pos="1760" data-local-id="bcaf763a8a8a"><strong data-renderer-mark="true">Orches

Skills