Senior Solutions Architect, Simulations - Clinical Sciences and Autonomous Lab

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.

• 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.
• Build 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.
• Design and deploy biomedical agentic AI systems, such as graph-based retrieval, multi‑hop clinical reasoning, and persistent agent memory.
• Keep up to date on AI advancements in healthcare, including domain‑specific models, robotics, and agentic frameworks.
• Engage with life science executives, IT leaders, data scientists, and developers to drive adoption of NVIDIA AI stack.
• Share your findings through training sessions, white papers, blog posts, and conference talks.

• 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, Lang Chain, 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.

• 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 Mu Jo Co  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.

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 Level4, and 224,000 USD–356,500 USD for Level
5.

You will also be eligible for equity and benefits.

NVIDIA is committed to fostering a diverse work environment and is proud to be an equal‑opportunity employer. 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.