NVIDIA

NVIDIA

Posted via Workday

Senior Solutions Architect, Simulations - Clinical Sciences and Autonomous Lab

Posted Aug 5, 2026

Role at a glance

Salary
$184K – $356.5K/yr
Location
2 Locations, California, United States
Work arrangement
On-site
Employment
Full-time
Experience
8+ years of experience.
Education
MS, PhD, or equivalent experience in Computer Science, Biomedical Engineering, Computational Biology, Computational Chemistry, Robotics,...

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Role Summary

AI-generated

The Senior Solutions Architect partners with healthcare and life sciences customers across North America to design, implement, and optimize GPU-accelerated AI software for clinical sciences, autonomous labs, biomanufacturing, and biomedical agentic AI. The role supports pharmaceutical companies, techbios, and software builders in adopting NVIDIA’s accelerated computing platforms and sharing technical findings with the broader community.

What You'll Do

  • Guide customers through requirements gathering, proof-of-concept development, deployment, integration, and ongoing optimization of...
  • Architect GPU-accelerated solvers for quantitative systems pharmacology and migrate scientific workloads from CPU to GPU.
  • Perform low-level CUDA optimization, including custom kernels for simulation and inference workloads in drug discovery.
  • Build physical AI and robotics solutions for autonomous labs and biomanufacturing, including sim-to-real VLA pipelines, real-time...
  • Design and deploy biomedical agentic AI systems involving graph-based retrieval, multi-hop clinical reasoning, and persistent agent memory.
  • Engage with life science executives, IT leaders, data scientists, and developers, and share findings through training sessions, white...

Generated from the employer's posting. Verify important details before applying.

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Qualifications

Requires applied software development experience in AI/ML, scientific computing, GPU acceleration, or robotics applied to healthcare or life sciences; experience in at least two focus areas; proficiency in Python and AI/ML frameworks; GPU deployment and scaling experience; and strong communication skills.

Required

  • Proven track record in software development for AI/ML, scientific computing, GPU acceleration, or robotics applied to healthcare or life...
  • Hands-on experience across at least two of the three focus areas: GPU-accelerated scientific simulation, sim-to-real robotics, and...
  • Proficiency in Python and AI/ML frameworks (PyTorch, LangChain, or custom)
  • 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

Preferred

  • Experience with C/C++ and 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...
  • Experience building, deploying, and evaluating agentic AI systems for healthcare—graph RAG over biomedical literature, long-memory...
  • Familiarity with NVIDIA libraries and platforms

Original job description

Content provided by the employer

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.

Applications for this job will be accepted at least until May 19, 2026.

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.

NVIDIA

About the company

NVIDIA

Large Enterprise

NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.