Senior Solutions Architect, Simulations - Clinical Sciences and Autonomous Lab

NVIDIA • US, CA, Remote, MA

2d • $184,000 - $356,500 • Onsite

About The Position

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!

Requirements

• 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.

Nice To Haves

• 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

Responsibilities

• 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.

Benefits

• equity
• benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Senior