NVIDIA is seeking a Senior Solutions Architect to drive innovation with healthcare and life sciences customers across North America, focusing on GPU-accelerated simulations for clinical sciences and autonomous labs. As a pioneer in accelerated computing, NVIDIA empowers pharmaceutical, biotech, and healthcare organizations to unlock new possibilities in patient modeling, laboratory and biomanufacturing robotic systems, and multi-agent reasoning. In this role, you will partner with leading pharmaceutical companies, techbios, and software builders to design, implement, and optimize GPU-accelerated AI software. If you are passionate about pushing the limits of accelerated computing in life sciences, we want to hear from you!
What you will be doing:
Guide customers through the end-to-end adoption of GPU-accelerated AI, from requirements gathering and proof-of-concept development to deployment, integration, and ongoing optimization.
Architect libraries such as GPU-accelerated solvers for quantitative systems pharmacology and CPU-to-GPU migration of scientific workloads.
Perform low-level CUDA optimization, including custom kernels to accelerate simulation and inference workloads in drug discovery
Building physical AI and robotics solutions for autonomous labs and biomanufacturing such as sim-to-real VLA pipelines, real-time control layers, and integration of perception, control, and policy stacks on NVIDIA platforms.
Designing and deploying biomedical agentic AI systems, such as graph-based retrieval, multi-hop clinical reasoning, and persistent agent memory
Keeping up to date on AI advancements in healthcare, including domain-specific models, robotics, and agentic frameworks.
Engaging with life science executives, IT leaders, data scientists, and developers to drive adoption of NVIDIA AI stack.
Sharing your findings through training sessions, white papers, blog posts, and conference talks.
What we need to see:
MS, PhD, or equivalent experience in Computer Science, Biomedical Engineering, Computational Biology, Computational Chemistry, Robotics, or related fields with strong applied experience.
8+ years of experience.
Proven track record in software development for AI/ML, scientific computing, GPU acceleration, or robotics applied to healthcare or life sciences.
Hands-on experience across at least two of the three focus areas: GPU-accelerated scientific simulation, sim-to-real robotics, and end-to-end agentic AI.
Proficiency in Python and AI/ML frameworks (PyTorch, LangChain, or custom). Experience with C/C++ and CUDA strongly preferred.
Experience deploying and scaling GPU-accelerated solutions in cloud or HPC environments (OCI, AWS, Azure, or on-prem clusters).
Excellent communication skills with the ability to present complex technical concepts to both technical and non-technical audiences.
Up to 20% travel may be required for on-site customer engagements.
Ways to stand out from the crowd:
Experience building GPU-accelerated scientific solvers, including low-level CUDA kernel optimization.
Background with sim-to-real robotics for life sciences—autonomous labs, biomanufacturing, surgical/clinical platforms—including MuJoCo or Isaac Sim, VLA pipelines, real-time control layers, and depth/RGB perception stacks.
Experience building, deploying, and evaluating agentic AI systems for healthcare—graph RAG over biomedical literature, long-memory agents, vision-based clinical event detection in production.
Familiarity with NVIDIA libraries and platforms
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 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.Skills Required
- MS, PhD, or equivalent experience in Computer Science, Biomedical Engineering, Computational Biology, or related fields
- 8+ years of experience in software development for AI/ML or scientific computing
- Proven track record in GPU acceleration or robotics applied to healthcare
- Hands-on experience in GPU-accelerated scientific simulation or sim-to-real robotics
- Proficiency in Python and AI/ML frameworks
- Experience with C/C++ and CUDA
- Experience deploying GPU-accelerated solutions in cloud or HPC environments
- Excellent communication skills to present technical concepts
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
-
Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
-
Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
-
Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
