NVIDIA
We are looking for a Solutions Architect in EMEA to collaborate with life sciences customers to accelerate digital biology use cases. You will work as a trusted technical advisor to pharmaceutical and tech‑bio organizations, helping them harness NVIDIA’s GPU‑based ML/AI and high‑performance computing platform to solve advanced scientific problems.
Responsibilities
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 optimisation.
Collaborate with business/account teams to identify technical needs, customer goals and strategies, and enable customer adoption of NVIDIA technology by mapping our solutions to their use cases.
Keep up to date on AI advancements in Digital Biology and relevant NVIDIA technologies that enable this innovation.
Provide technical leadership, offering vision for integrating NVIDIA technology into AI and HPC architectures for advanced applications such as agentic AI, autonomous labs or drug discovery.
Engage developers, researchers, data scientists, IT managers and senior leaders internally and externally to gain experience across technical domains.
Document knowledge and teach others—build targeted training, write whitepapers, blogs or wiki articles, and work through challenging problems with customers.
Utilise conferencing tools and travel as required to support customers and drive success.
Qualifications
MS or PhD (or equivalent experience) in Computer Science, Computational Biology, Computational Chemistry, 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 custom frameworks) applied to scientific questions.
Strong time‑management and organisational skills for coordinating multiple initiatives and implementing new technology in complex projects.
Motivated self‑starter with effective problem‑solving and customer‑facing communication skills, able to present complex technical information to innovative individuals.
Ways to Stand Out
Experience in AI‑at‑scale for multi‑omics foundation models, protein structure prediction, drug discovery or clinical development.
Experience building, deploying and optimising agentic AI systems for healthcare and life sciences, particularly for scientific software vendors or data platforms.
Experience developing, training and customizing Transformer models for healthcare and life sciences using libraries such as Transformer Engine or Megatron‑LM.
Background in accelerating scientific algorithms with CUDA, distributed programming for supercomputing, AI deployment/inference technologies (TensorRT), cloud deployment (AWS, Azure) or optimisation frameworks (cuOpt).
Experience in the pharmaceutical industry or established thought leadership through publications or presentations on AI/ML applications in healthcare and life sciences.
NVIDIA is committed to fostering a diverse work environment and is an equal‑opportunity employer. We do not discriminate on the basis of race, religion, colour, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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Responsibilities
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 optimisation.
Collaborate with business/account teams to identify technical needs, customer goals and strategies, and enable customer adoption of NVIDIA technology by mapping our solutions to their use cases.
Keep up to date on AI advancements in Digital Biology and relevant NVIDIA technologies that enable this innovation.
Provide technical leadership, offering vision for integrating NVIDIA technology into AI and HPC architectures for advanced applications such as agentic AI, autonomous labs or drug discovery.
Engage developers, researchers, data scientists, IT managers and senior leaders internally and externally to gain experience across technical domains.
Document knowledge and teach others—build targeted training, write whitepapers, blogs or wiki articles, and work through challenging problems with customers.
Utilise conferencing tools and travel as required to support customers and drive success.
Qualifications
MS or PhD (or equivalent experience) in Computer Science, Computational Biology, Computational Chemistry, 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 custom frameworks) applied to scientific questions.
Strong time‑management and organisational skills for coordinating multiple initiatives and implementing new technology in complex projects.
Motivated self‑starter with effective problem‑solving and customer‑facing communication skills, able to present complex technical information to innovative individuals.
Ways to Stand Out
Experience in AI‑at‑scale for multi‑omics foundation models, protein structure prediction, drug discovery or clinical development.
Experience building, deploying and optimising agentic AI systems for healthcare and life sciences, particularly for scientific software vendors or data platforms.
Experience developing, training and customizing Transformer models for healthcare and life sciences using libraries such as Transformer Engine or Megatron‑LM.
Background in accelerating scientific algorithms with CUDA, distributed programming for supercomputing, AI deployment/inference technologies (TensorRT), cloud deployment (AWS, Azure) or optimisation frameworks (cuOpt).
Experience in the pharmaceutical industry or established thought leadership through publications or presentations on AI/ML applications in healthcare and life sciences.
NVIDIA is committed to fostering a diverse work environment and is an equal‑opportunity employer. We do not discriminate on the basis of race, religion, colour, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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