Role at a glance
- Salary
- $184K – $287.5K/yr
- Location
- Remote - US - California
- Work arrangement
- Remote
- Employment
- Full-time
- Experience
- 8+ years of hands-on experience in accelerated computing and knowledge of parallel computing with GPUs
- Education
- BS, MS or PhD in Computational Physics, Engineering, Computer Science, Applied Mathematics, or a related field, or equivalent experience
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Role Summary
The Solutions Architect will join NVIDIA’s Higher Education and Research Team as a technical partner to universities and research institutes. The role supports computational physics, engineering simulation, scientific AI, and high-performance computing workflows using NVIDIA accelerated computing platforms.
What You'll Do
- Partner with research universities and institutes to co-create HPC and AI solutions using NVIDIA’s accelerated computing platform
- Collaborate with engineering, product, and business teams to align NVIDIA’s technical roadmap with scientific and engineering research...
- Engage with developers and researchers to architect solutions for computational physics, multiphysics simulation, engineering design...
- Help researchers move from high-fidelity simulation data to AI-enabled workflows, including surrogate models, neural operators,...
- Profile and optimize scientific applications, AI training, and inference workloads on accelerated systems
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
BS, MS or PhD in Computational Physics, Engineering, Computer Science, Applied Mathematics, or a related field, or equivalent experience; 8+ years of hands-on experience in accelerated computing and knowledge of parallel computing with GPUs; experience porting and/or optimizing scientific or engineering applications targeting GPUs; strong fundamentals in programming and software design, especially in Python and C++; familiarity with computational physics or engineering simulation workflows; excellent knowledge of the theory and practice of AI at scale.
Required
- BS, MS or PhD in Computational Physics, Engineering, Computer Science, Applied Mathematics, or a related field, or equivalent experience
- 8+ years of hands-on experience in accelerated computing and knowledge of parallel computing with GPUs
- Experience porting and/or optimizing scientific or engineering applications targeting GPUs
- Strong fundamentals in programming and software design, especially in Python and C++
- Familiarity with computational physics or engineering simulation workflows, including numerical methods, model validation,...
- Excellent knowledge of the theory and practice of AI at scale, especially as applied to scientific, simulation, or physics-based workloads
- A dedication to clear and inclusive communication with a deep desire to partner with the academic community to help others succeed in...
Preferred
- Excellent GPU programming skills, including debugging, profiling, code optimization, performance analysis, and test design
- Experience supporting HPC, AI, computational physics, engineering simulation, or scientific computing workflows
- Familiarity with NVIDIA scientific computing and AI tools such as PhysicsNeMo, NVIDIA Warp, PyTorch, JAX, or related frameworks
- Experience building AI-enabled simulation workflows using neural operators, physics-informed models, graph neural networks, and/or...
Original job description
Content provided by the employer
Original job description
Content provided by the employer
At NVIDIA, we believe that accelerated computing is key to solving the world’s most significant scientific and engineering challenges. We are looking for a Solutions Architect to join our Higher Education and Research Team, where you will serve as a technical partner to the visionaries shaping the future of discovery!
In this role, you will be an integral part of a team supporting higher education universities and research institutes across the nation, with a focus on computational physics, engineering simulation, scientific AI, and high-performance computing. You will help researchers harness NVIDIA platforms to accelerate simulation, build trusted AI surrogates, train scientific foundation models, and unlock new workflows in areas such as fluid dynamics, multiphysics simulation, engineering design exploration, and physics-based modeling at scale. If reading this gets you excited and energized to help researchers solve hard computational physics and engineering problems, then we would love to meet you.
What you'll be doing:
Partner with research universities and institutes to co-create innovative HPC and AI solutions using NVIDIA’s accelerated computing platform
Collaborate with engineering, product, and business teams to align NVIDIA’s technical roadmap with the evolving strategies and complex workflows of the scientific and engineering research community
Engage with developers and researchers to architect ground-breaking solutions in areas such as computational physics, multiphysics simulation, engineering design exploration, and the next generation of Scientific Foundation Models
Help researchers move from high-fidelity simulation data to AI-enabled workflows, including surrogate models, neural operators, physics-informed models, reduced-order models, differentiable simulation, and real-time inference
Profile and optimize the performance of scientific applications, AI training, and inference workloads so sophisticated research workflows reach their full potential on accelerated systems
Travel requirement up to 20%
What we need to see:
BS, MS or PhD in Computational Physics, Engineering, Computer Science, Applied Mathematics, or a related field, or equivalent experience
8+ years of hands-on experience in accelerated computing and knowledge of parallel computing with GPUs
Experience porting and/or optimizing scientific or engineering applications targeting GPUs
Strong fundamentals in programming and software design, especially in Python and C++
Familiarity with computational physics or engineering simulation workflows, including numerical methods, model validation, uncertainty/error analysis, or simulation-data pipelines
Excellent knowledge of the theory and practice of AI at scale, especially as applied to scientific, simulation, or physics-based workloads
A dedication to clear and inclusive communication with a deep desire to partner with the academic community to help others succeed in their research goals
Ways to stand out from the crowd:
Excellent GPU programming skills, including debugging, profiling, code optimization, performance analysis, and test design
Experience supporting HPC, AI, computational physics, engineering simulation, or scientific computing workflows.
Familiarity with NVIDIA scientific computing and AI tools such as PhysicsNeMo, NVIDIA Warp, PyTorch, JAX, or related frameworks
Experience building AI-enabled simulation workflows using neural operators, physics-informed models, graph neural networks, and/or reduced-order models.
A desire to learn and grow within an encouraging, forward-thinking community dedicated to solving the world’s most significant computational science and engineering challenges
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
#NALASAHiring
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.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.
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.