NVIDIA DGX Expert
Posted 10 hours 7 minutes ago by NXTminds
Interim AI & ML Engineer - NVIDIA DGX Expert
Join one of Europe's most advanced AI infrastructure programmes and help accelerate scientific discovery and industrial innovation. We are looking for a hands-on AI/ML engineer with deep experience in NVIDIA DGX systems (preferably B200 or H100) to help onboard and optimise AI workloads for our next-gen supercomputing facility.
Why This Is Unique
You'll be part of a European Centre of Excellence for AI, working with one of the most powerful academic AI infrastructures available. You'll directly contribute to breakthroughs in areas like cancer research, and help shape how large-scale AI is built, shared, and scaled in a real-world setting.
About the Role
You'll join a core team that supports researchers and industrial partners in deploying and scaling their AI projects on a unique DGX B200 Basepod infrastructure. Your focus is on productionalising AI workloads-not maintaining the cluster itself. The environment is already operational and maintained by a dedicated HPC team. What we need is a specialist who can make the most out of the NVIDIA software ecosystem and empower others to do the same.
This role requires close day-to-day collaboration with internal teams-so we're looking for someone based in or near Europe and available during standard CET working hours.
What You'll Do
- Support onboarding of current and future AI projects-academic and industrial
- Guide teams in efficiently setting up and scaling AI workloads on the DGX Basepod
- Use the NVIDIA Software Building Blocks (e.g. AI Enterprise, Base Command, Run:ai) to optimise training pipelines
- Collaborate with ML researchers to productionalise their workflows using best practices in compute orchestration
- Train core team members on tooling, design patterns and performance tuning
- Act as a bridge between cutting-edge hardware and practical ML application
What We're Looking For
- Proven experience working directly with NVIDIA DGX B200 or H100 systems
- Strong understanding of NVIDIA's software ecosystem for AI development (AI Enterprise, Run:ai, RAPIDS, etc.)
- Solid background in ML Engineering, AI workload orchestration, and GPU resource optimisation
- Comfortable working with Kubernetes-based AI environments, especially in an HPC context
- Ability to collaborate on-site or hybrid during European office hours (CET)
- Strong communication skills and a mentoring mindset