Job description

NVIDIA is seeking a Senior Solutions Architect to help redefine drug discovery and biological research through GPU-accelerated AI. This role will focus on enabling pharmaceutical and techbio customers to train, optimize, and deploy large biological foundation models using NVIDIA’s accelerated computing platform, models and libraries. Our Solutions Architects are elite developers, scientists, and technical leaders who thrive at the intersection of science, AI, and customer engagement. As a trusted technical advisor, you will work with leading organizations across North America to accelerate AI/ML workflows in areas such as genomics, quantum chemistry, biomaterials science, and structural biology. You will help customers integrate accelerated libraries, scalable training frameworks, and high-performance computing techniques to improve training efficiency, reduce time to insight, and unlock new scientific capabilities. What you will be doing: • Partner with business and account teams to understand customer goals, scientific workflows, technical needs, and platform adoption strategies. • Architect and optimize AI/ML pipelines for training large biological foundation models, with a focus on BioNeMo libraries and GPU-accelerated software that improve training efficiency. • Build proof-of-concept demonstrations that show how NVIDIA software and hardware accelerate scientific discovery. • Collaborate across NVIDIA with subject matter experts, engineering, product, and field teams to bring the right technical expertise to customer engagements and deliver high-impact solutions. • Document best practices and teach others through technical enablement, partner training, whitepapers, blogs, internal wiki articles, and hands-on customer workshops. • Serve as a trusted technical advisor for integrating NVIDIA technologies into advanced biopharma and diagnostics applications. What we need to see: • MS or PhD in Computational Biology, Computational Chemistry, Computational Physics, Chemical Engineering, Biophysics, Computer Science, or a related technical field (or equivalent experience). • 5+ years of experience in software development for deep learning, GPU acceleration, or scientific computing applications. • Hands-on experience applying ML to at least one of these domains: genomics, quantum chemistry, biomaterials science, or structural biology. • Experience profiling and optimizing training workflows for large AI models, including performance tuning, distributed training, data pipelines, and GPU utilization. • Proficiency with Linux environments and experience working in HPC or accelerated computing environments, including Slurm and/or Kubernetes-based clusters. • Excellent communication skills, especially for presenting highly technical material to scientists, engineers, executives, and customer stakeholders. • A passion for working with forward-thinking customers, learning continuously, and staying at the forefront of AI for life sciences. Ways to stand out from the crowd: • Background with BioNeMo, NeMo, or related NVIDIA frameworks for training large biological or scientific foundation models. • Experience with Parabricks, RAPIDS-singlecell, ALCHEMI, cuEquivariance, cuEST, or related accelerated libraries. • Experience working with pharmaceutical or biotech companies • Demonstration of customer-facing technical leadership, including architecture reviews, executive briefings, technical workshops, or deployments at lighthouse accounts. NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until September 4, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Requirements

Must-haves

Partner with business and account teams to understand customer goals, scientific workflows, technical needs, and platform adoption strategies.
Architect and optimize AI/ML pipelines for training large biological foundation models, with a focus on BioNeMo libraries and GPU-accelerated software that improve training efficiency.
Build proof-of-concept demonstrations that show how NVIDIA software and hardware accelerate scientific discovery.
Collaborate across NVIDIA with subject matter experts, engineering, product, and field teams to bring the right technical expertise to customer engagements and deliver high-impact solutions.
Document best practices and teach others through technical enablement, partner training, whitepapers, blogs, internal wiki articles, and hands-on customer workshops.
Serve as a trusted technical advisor for integrating NVIDIA technologies into advanced biopharma and diagnostics applications.
MS or PhD in Computational Biology, Computational Chemistry, Computational Physics, Chemical Engineering, Biophysics, Computer Science, or a related technical field (or equivalent experience).
5+ years of experience in software development for deep learning, GPU acceleration, or scientific computing applications.
Hands-on experience applying ML to at least one of these domains: genomics, quantum chemistry, biomaterials science, or structural biology.
Experience profiling and optimizing training workflows for large AI models, including performance tuning, distributed training, data pipelines, and GPU utilization.
Proficiency with Linux environments and experience working in HPC or accelerated computing environments, including Slurm and/or Kubernetes-based clusters.
Excellent communication skills, especially for presenting highly technical material to scientists, engineers, executives, and customer stakeholders.
A passion for working with forward-thinking customers, learning continuously, and staying at the forefront of AI for life sciences.
Background with BioNeMo, NeMo, or related NVIDIA frameworks for training large biological or scientific foundation models.
Experience with Parabricks, RAPIDS-singlecell, ALCHEMI, cuEquivariance, cuEST, or related accelerated libraries.
Experience working with pharmaceutical or biotech companies
Demonstration of customer-facing technical leadership, including architecture reviews, executive briefings, technical workshops, or deployments at lighthouse accounts.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until September 4, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlkubernetes

Platform: eightfold
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