Applied AI solutions engineer on cloud infrastructure

Nebius Group; Amsterdam; On-site; EUR 95,000 - 140,000; Full time

Benefits offered by this job

Competitive salary

Flexible working

International environment

Team collaboration

Job summary

Nebius Group is shaping a new era in cloud infrastructure for the global AI economy. You will build prototypes and demos across the product portfolio, supporting customers through POC design, onboarding, and validation, acting as the bridge between their ML teams and the Nebius platform.

You’ll push the boundaries of applied AI and translate findings into actionable product feedback. Ideal candidates have hands-on experience with LLMs, distributed training, and modern ML stacks, plus strong

Qualifications

• Experience fine-tuning large models and debugging distributed training pipelines.
• Proven ability to build production ML prototypes and POCs for customer onboarding.
• Familiarity with MLOps at scale and cloud-based AI infrastructure.

Responsibilities

• Build prototypes and demos across the product portfolio for sales and engineering teams.
• Support new customers with POC design, onboarding, and validation.
• Contribute to product roadmap with grounded customer feedback and technical insights.
• Develop reusable assets like notebooks and reference architectures.

Skills

LLM fine-tuning

Distributed training

MLOps

Customer-facing prototyping

Tools

PyTorch

HuggingFace

CUDA fundamentals

Kubernetes (ML)

MLflow

Vector databases

Job description

Описание

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.

Задачи

Build prototypes and demos across the product portfolio - serverless inference, databases, MLflow, MLOps, and vertical use cases in Physical AI and HCLS - that become assets for sales, product, and engineering teams. Support new customers hands-on through POC design, technical onboarding, and validation; act as the bridge between their ML team and the platform during the critical first months. Go deep on emerging applied AI - new training techniques, inference optimizations, agentic architectures, new frameworks - and turn findings into working prototypes, writeups, and product recommendations. Feed the product roadmap with specific, grounded feedback; be the voice of "here's what broke in three customer POCs last month and here's what needs to change". Develop reusable technical assets - notebooks, reference architectures, benchmark results - that reduce onboarding friction at scale.

Требования

You've fine-tuned large models, debugged distributed training jobs, built production RAG or agentic pipelines, and optimized inference on GPU infrastructure - not just read about it. You're fluent in the modern ML stack: PyTorch, HuggingFace, CUDA fundamentals, Kubernetes for ML, MLflow or equivalent, vector databases. You've worked with enterprise ML teams - whether as a solutions engineer, customer engineer, or an ML engineer who collaborated closely with customers. You read papers and implement them - not for credit, but because it's how you stay sharp. You communicate with calibration: you can explain activation checkpointing tradeoffs to an ML engineer in the morning and the cost implication to a CTO in the afternoon. Будет плюсом: Experience in any of our vertical domains: Physical AI / robotics / simulation, HCLS (drug discovery, medical imaging, clinical NLP), or enterprise AI application development; Familiarity with MLOps at scale (Kubeflow, Metaflow, Argo, Ray); Prior work at a cloud provider or AI infrastructure company; You've shared technical work publicly - notebooks, talks, blog posts that people actually use.

Условия

Competitive salary and comprehensive benefits package. Opportunities for professional growth within Nebius. Flexible working arrangements. A dynamic and collaborative work environment that values initiative and innovation. We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law. Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI.