NVIDIA
healthcare and life sciences
SeniorSolutionsArchitect,SimulationsClinicalSciencesandAutonomousLab
“Senior Solutions Architect, Simulations - Clinical Sciences and Autonomous Lab at NVIDIA. Skills: GPU-accelerated simulations, clinical sciences, autonomous labs, AI software, GPU-accelerated AI, scientific simulation, sim-to-real robotics, agentic AI. drive innovation with healthcare and life sciences customers. design, implement, and optimize GPU-accelerated AI software”
Industry & Context.
Up to 20% travel may be required for on-site customer engagements
What They're Looking For.
Must Have
MS, PhD, or equivalent experience in Computer Science, Biomedical Engineering, Computational Biology, Computational Chemistry, Robotics, or related fields with 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, 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 Have
Experience with AI/ML frameworks (PyTorch, LangChain, or custom), Experience with C/C++, Experience with CUDA, 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
What You'll Do.
drive innovation with healthcare and life sciences customers
and optimize GPU-accelerated AI software
guide customers through the end-to-end adoption of GPU-accelerated AI
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
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
and agentic frameworks
engaging with life science executives
and developers to drive adoption of NVIDIA AI stack
sharing your findings through training sessions
How You'll Work.
Team & Collaboration
partner with leading pharmaceutical companies, techbios, and software builders; Engaging with life science executives, IT leaders, data scientists, and developers
Communication Scope
Excellent communication skills with the ability to present complex technical concepts to both technical and non-technical audiences
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