below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$161,709–$235,750.
Based on 240 similar postings.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
1623 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 1110 roles with salary data.
NVIDIA is seeking a Senior Solutions Architect to help redefine drug discovery and biological research through GPU-accelerated AI. In this role, you will serve as a trusted technical advisor for pharmaceutical and techbio customers, architecting and optimizing AI/ML pipelines to train, optimize, and deploy large biological foundation models. You will build proof-of-concept demonstrations, document best practices, and lead technical enablement for workflows in genomics, quantum chemistry, biomaterials science, and structural biology. Required skills include proficiency with Linux, HPC environments, Slurm, and Kubernetes-based clusters, alongside experience in deep learning, GPU acceleration, and scientific computing. You will specifically utilize BioNeMo libraries, Parabricks, RAPIDS-singlecell, ALCHEMI, cuEquivariance, and cuEST to improve training efficiency and reduce time to insight for advanced biopharma and diagnostics applications.
What does a Solutions Architect earn in California?
Median $235750 from 57 postings across 11 companies.
Architect and optimize AI/ML pipelines for training large biological foundation models using GPU-accelerated software.
Build proof-of-concept demonstrations showing how NVIDIA hardware and software accelerate scientific discovery.
Serve as a technical advisor for integrating NVIDIA technologies into biopharma and diagnostics applications.
Partner with business teams to define customer goals, scientific workflows, and platform adoption strategies.
Document best practices and provide technical enablement through whitepapers, blogs, and hands-on workshops.
Integrate accelerated libraries and scalable training frameworks to improve training efficiency and reduce time to insight.
What we're looking for
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 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 for presenting highly technical material to scientists, engineers, executives, and customer stakeholders.
Background with BioNeMo, NeMo, or related NVIDIA frameworks for training large biological or scientific foundation models (preferred).
Experience with Parabricks, RAPIDS-singlecell, ALCHEMI, cuEquivariance, cuEST, or related accelerated libraries (preferred).
Remote (Santa Clara, CA)+360 days ago
$184,000–$287,500
GPU
HPC
AI
ML
GenAI
NVIDIA Hardware
NCCL
DCGM
UFM
Mission Control
Base Command Manager
SLURM
K8s
Data Center Design
Cluster Administration
Performance Testing
AI Benchmarking
AWS
Microsoft Azure
Google Cloud Platform
Cloud Computing
Microservices
SaaS
PaaS
IaaS
Agile
Full-stack Development
System Design
Network Diagrams
Security Controls
Digital Transformation
Software Development
AWS
Microsoft Azure
Google Cloud Platform
Cloud Computing
Microservices
SaaS
PaaS
IaaS
Agile
Full-stack Development
System Design
Network Diagrams
Security Controls
Digital Transformation