Senior Solutions Architect – Drug Discovery

NVIDIA

Senior Solutions Architect at NVIDIA focused on drug discovery and biological research through GPU-accelerated AI. Collaborating with pharmaceutical and techbio clients to enhance AI/ML workflows across North America.

Posted 5/16/2026full-timeCalifornia, Massachusetts • 🇺🇸 United StatesSenior💰 $184,000 - $287,500 per yearWebsite

Tech Stack

Tools & technologies

KubernetesLinux

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

MS or PhD in Computational Biology, Computational Chemistry, Computational Physics, Chemical Engineering, Biophysics, Computer Science, or a related technical field (or equivalent experience).
8+ 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.

Benefits

Comp & perks

equity
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Hard Skills & Tools

AI/ML pipelinesBioNeMo librariesGPU accelerationdeep learningscientific computingperformance tuningdistributed trainingdata pipelinesLinux environmentsHPC

Soft Skills

communication skillstechnical enablementcollaborationcustomer engagementtrainingdocumentationpresentation skillstrustworthinessadaptabilitypassion for learning