NVIDIA

2 months ago

Senior Solutions Architect, Simulations - Clinical Sciences and Autonomous Lab

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Lead GPU-accelerated simulations and AI solutions for healthcare and life sciences, partnering with pharma and biotech customers to design, optimize, and deploy CUDA-accelerated workloads and autonomous lab robotics on NVIDIA platforms. Drive adoption of the NVIDIA AI stack, build end-to-end workflows, and communicate complex technical concepts to diverse audiences across NA.

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Key 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.
•Build physical AI and robotics solutions for autonomous labs and biomanufacturing, including sim-to-real pipelines and integration of perception, control, and policy stacks.
•Design and deploy biomedical agentic AI systems, such as graph-based retrieval and multi-hop clinical reasoning, with persistent agent memory.

Travel: Low travel

Pay and Benefits

Equity and Bonus:Equity

Perks:Equity

Key Requirements

•MS, PhD, or equivalent experience in Computer Science, Biomedical Engineering, Computational Biology, Computational Chemistry, Robotics, or related fields
•8+ years of experience in software development for AI/ML, scientific computing, GPU acceleration, or robotics
•Proficiency in Python; experience with AI/ML frameworks (PyTorch, LangChain, or similar); strong preference for C/C++ and CUDA
•Experience deploying and scaling GPU-accelerated solutions in cloud or HPC environments (OCI, AWS, Azure, or on-prem clusters)
•Excellent communication skills to present complex concepts to technical and non-technical audiences

Experience:8+ yearsHealthcareLife sciencesAIGPURobotics

Skills:PythonC++CUDAPyTorchLangChainGPUHPCCloud

Languages:English

Tech Stack:CUDAPyTorchLangChainOCIAWSAzureOn-prem

Company Brief

NVIDIA

Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor

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NVIDIA

2 months ago

Senior Solutions Architect, Simulations - Clinical Sciences and Autonomous Lab

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Key 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.
•Build physical AI and robotics solutions for autonomous labs and biomanufacturing, including sim-to-real pipelines and integration of perception, control, and policy stacks.
•Design and deploy biomedical agentic AI systems, such as graph-based retrieval and multi-hop clinical reasoning, with persistent agent memory.

Travel: Low travel

Pay and Benefits

Equity and Bonus:Equity

Perks:Equity

Key Requirements

•MS, PhD, or equivalent experience in Computer Science, Biomedical Engineering, Computational Biology, Computational Chemistry, Robotics, or related fields
•8+ years of experience in software development for AI/ML, scientific computing, GPU acceleration, or robotics
•Proficiency in Python; experience with AI/ML frameworks (PyTorch, LangChain, or similar); strong preference for C/C++ and CUDA
•Experience deploying and scaling GPU-accelerated solutions in cloud or HPC environments (OCI, AWS, Azure, or on-prem clusters)
•Excellent communication skills to present complex concepts to technical and non-technical audiences

Experience:8+ yearsHealthcareLife sciencesAIGPURobotics

Skills:PythonC++CUDAPyTorchLangChainGPUHPCCloud

Languages:English

Tech Stack:CUDAPyTorchLangChainOCIAWSAzureOn-prem

Company Brief

NVIDIA

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor