Specialist Solutions Architect (Life Sciences)

The team

Customer experience at Nebius GPU AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions. Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community.

The role

We are looking for an experienced Specialist Solutions Architect (Life Sciences) to support our customers in academia, biotech, and pharmaceutical industries as they harness Nebius services for cutting-edge scientific research and innovation. This role is ideal for someone with a strong academic background—preferably a PhD—in a life sciences or related discipline, and a deep interest in applying AI and high-performance computing (HPC) to real-world scientific challenges.

In this role, you will act as a trusted advisor, collaborating closely with research teams, data scientists, and bioinformaticians to architect scalable AI and data solutions for complex scientific workloads—from genomics and molecular modeling to large-scale simulations and machine learning-driven drug discovery.

You’re welcome to work in our office in Amsterdam or remotely from any EU country.

Your responsibilities will include: 

• Design tailored solutions for life sciences customers that meet both scientific and business objectives.
• Guide researchers and technical stakeholders in leveraging Nebius infrastructure for AI/ML, HPC, and data-intensive workflows.
• Build and maintain long-term, trust-based relationships with academic and scientific institutions.
• Deliver technical presentations, write whitepapers, and host webinars/workshops for audiences across the spectrum of scientific expertise.
• Collaborate with Nebius engineering and product teams to relay feedback from the scientific community and influence feature development.

We expect you to have: 

• PhD or equivalent research experience in bioinformatics, computational biology, cheminformatics, structural biology, or a related scientific field.
• 3+ years of experience with cloud technologies, preferably in MLOps, scientific computing, or AI/ML engineering roles.
• Strong understanding of life sciences workflows (e.g., omics analysis, molecular dynamics, protein structure prediction, AI/ML in drug discovery).
• Proven experience in distributed training or simulation workloads (multi-node, multi-GPU environments).
• Hands-on knowledge of scientific computing libraries and ML frameworks such as PyTorch, JAX, or TensorFlow.
• Excellent communication skills, especially in explaining technical concepts to scientific audiences.
• Bonus Points
• Experience deploying inference or simulation infrastructure in production or research environments.
• Ability to transition scientific prototypes or pipelines from proof-of-concept to scalable production systems.
• Familiarity with open-source tools and datasets commonly used in life sciences research.

Preferred Tooling:

Languages: Python, Go, C++, Java
Orchestration: Kubernetes (K8s), Slurm
DevOps Tools: Git, Docker, Helm
Infrastructure as Code: Terraform
ML & HPC Frameworks: PyTorch, TensorFlow, JAX, HuggingFace, Biopython, RDKit, Scikit-learn