Solution Architect – Digital Biology

Solution Architect – Digital Biology

Join our team as a Solutions Architect in EMEA, where you will collaborate with life sciences customers to accelerate digital biology use cases. At NVIDIA, we have a group of exceptional developers and scientists who thrive on working with the latest GPU hardware and software. Our platform for ML/AI and high-performance computing has already had a significant impact on the healthcare industry, serving leading pharmaceutical companies, academic medical centers, and start-ups.

We are seeking an enthusiastic individual to join us in exploring new opportunities in the AI-powered digital biology revolution. As a Solution Architect, you will work as a trusted technical advisor to customers in the pharmaceutical and techbio industries, who envision accelerated computing and artificial intelligence as a transformative force in their field. Join us on this thrilling journey and advance your career while empowering top organizations and institutions worldwide.

• Guide customers through the end-to-end process of AI adoption—from requirements gathering and proof-of-concept development to deployment, integration, benchmarking and ongoing optimization.
• Collaborate with our business/account team to identify technical needs, customer goals, and strategies. Your responsibilities will include enabling customer adoption of NVIDIA technology by mapping our solutions to their use cases and driving positive relationships with our technology partners, making NVIDIA an integral part of end-user solutions.
• Keep up to date on AI advancements in Digital Biology as well as relevant NVIDIA technology that enable this innovation.
• Be a technical leader, bringing vision to the integration of NVIDIA technology into AI and HPC architectures for advanced applications, such as agentic AI, autonomous labs or drug discovery.
• Engage with developers, researchers, data scientists, IT managers, and senior leaders internally and externally to gain experience in various technical areas.
• Document what you know and teach others. This can vary from building targeted training for partners and other Solutions Architects to writing whitepapers, blogs, and wiki articles to simply working through hard problems with a customer on a whiteboard.
• We make heavy use of conferencing tools, but some travel is required for this role. You are empowered to find the best way to get your job done and make our customers successful.

• MS or PhD (or equivalent experience) in Computer Science, Computational Biology, Computational Chemistry or Computational Physics, or related fields with strong applied experience in these domains.
• 5+ years of work-related experience with hands‑on expertise in AI/ML for healthcare or life sciences.
• Proven experience with Python and AI/ML frameworks (PyTorch, Langchain, or building custom framework) and application to scientific questions.
• Strong time-management and organizational skills for coordinating multiple initiatives, priorities, and implementations of new technology and products into very complex projects.
• Motivated self-starter with an equal balance of strong problem-solving skills and customer-facing communication skills – especially in effectively presenting complex technical information. Must enjoy engaging with innovative individuals, continuous learning, and staying at the forefront of the field.

• Demonstrated work in AI‑at‑scale related to multi‑omics foundation models, protein structure prediction, drug discovery or clinical development.
• Experience building, deploying, and optimizing agentic AI systems for healthcare and life sciences, especially for scientific software vendors and data platforms, is a plus.
• Experience developing, training and customizing Transformer models for healthcare and life sciences applications, especially using libraries like Transformer Engine or Megatron‑LM.
• Background with accelerating scientific algorithms using parallel programming (e.g., using CUDA), or experience with distributed programming models for supercomputing applications, AI deployment/inference technologies (e.g. Tensor
  
  RT), cloud…