Senior Solutions Architect – Simulations, Clinical Sciences, Autonomous Lab

🕒 May 16

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Logo of NVIDIA

NVIDIA

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

Artificial Intelligence • Gaming • Automotive

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• 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 findings through training sessions, white papers, blog posts, and conference talks.

🎯 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. • Up to 20% travel may be required for on-site customer engagements.

🏖️ Benefits

• Eligible for equity and benefits

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