Why work at Nebius
Nebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.
Where we work
Headquartered in Amsterdam and listed on Nasdaq, Nebius has a global footprint with R&D hubs across Europe, North America, and Israel. The team of over 800 employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&D team.
- Be a center of ML/AI expertise for both dev and business teams.
- Own the backlog of 1–3 AI/ML products.
- Make technical requirements for IaaS and PaaS teams that are essential for your products.
- Introduce and promote products to the market in collaboration with cross-functional teams.
- Make materials and onboarding guides for Solution Architect teams and Sales.
- Be an internal customer for a Marketplace and Solution Architects teams to build E2E scenarios using our products.
Requirements:
- We expect the candidate to be the best user of the product they manage, so technical expertise is mandatory.
- Have solid experience as an ML Engineer/MLOps Engineer/AI Engineer with one or more domains from the following list:
Organizing ML infrastructure using best MLOps practices with instruments like MLflow, W&B, MosaicML, Kubeflow, Apache Airflow, ClearML, AzureML, SageMaker, VertexAI
Maintaining and optimizing a large inference cluster with KServe, vLLM, Triton, RunAI, Seldon
Experience using of data preparation tools like Databricks and Apache Spark
Building a product on top of LLMs that leverages techniques such as RAG, fine-tuning, and function calling, with an understanding of continuous eval of the quality
- Product management experience is not required but willingness to learn is essential.
- You have experience as an ML engineer, specializing in developing large generative AI models. You are now eager to shift your focus toward creating tools and instruments that enhance the efficiency of such teams.
- You have worked as an MLOps, Solution Architect or DevOps engineer, providing infrastructure for ML teams and delving deeply into ML specifics. You are keen to share your expertise through product development and know how to build MLOPS based on serverless GPU services such as Modal, Cerebrius and Google Cloud Run.
- You have a background as an ML engineer and transitioned to product management, with a proven track record of delivering complex products for tech customers.
What we offer
- Competitive salary and comprehensive benefits package.
- Opportunities for professional growth within Nebius.
- Hybrid working arrangements.
- A dynamic and collaborative work environment that values initiative and innovation.
We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us!
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What We Do
Cloud platform specifically designed to train AI models
