Senior Applied AI Solutions Engineer
Nebius Group
full-time
Posted on:
Location Type: Remote
Location: Netherlands
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Job Level
Tech Stack
About the role
- 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.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
fine-tuning large modelsdebugging distributed training jobsbuilding production RAG pipelinesoptimizing inference on GPU infrastructuremodern ML stackPyTorchHuggingFaceCUDA fundamentalsKubernetes for MLMLflow
Soft Skills
communicationcalibrationcustomer collaborationtechnical onboardingfeedback provision