Senior Applied AI Solutions Engineer

Job not on LinkedIn

🕒 March 16

🇳🇱 Netherlands – Remote

⏰ Full Time

🟠 Senior

💻 Solutions Engineer

👻 Ghost score 55%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Nebius Group

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🤖 Artificial Intelligence

🏢 Enterprise

☁️ SaaS

Artificial Intelligence • Enterprise • SaaS

Nebius Group is building one of the world’s leading AI infrastructure companies, focusing on providing the necessary compute, storage, and tools for developers in the AI space. Based in Europe and listed on Nasdaq, Nebius has a global presence with R&D centers across Europe, North America, and Israel. The company's primary offering is an AI-centric cloud platform designed for intensive AI workloads, complemented by various other businesses involved in generative AI development, edtech, and autonomous technology.

📋 Description

• 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

🎯 Requirements

• 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.

🏖️ Benefits

• 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.