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Ai For Science information

How does collaboration typically work between AI for Science professionals and domain experts in research teams?

AI for Science professionals frequently work closely with experts in fields such as biology, chemistry, or physics to identify scientific problems that can benefit from machine learning techniques. Collaboration usually involves regular meetings to translate complex scientific challenges into data-driven models, sharing domain knowledge, and iteratively refining solutions. Effective communication and a willingness to bridge gaps between computational and scientific perspectives are essential. This interdisciplinary teamwork not only enhances the impact of AI solutions but also fosters ongoing learning and innovation.

What is AI for Science?

AI for Science refers to the application of artificial intelligence and machine learning techniques to accelerate scientific discovery and research. By leveraging large datasets, complex models, and advanced computational methods, AI helps scientists analyze data, identify patterns, simulate experiments, and make predictions across various scientific fields such as biology, chemistry, physics, and climate science. This approach can significantly speed up research, uncover new insights, and solve problems that were previously too complex or time-consuming for traditional methods.

Which AI for science is best?

The best AI tools for science depend on the specific application, such as data analysis, modeling, or simulation. Popular options include TensorFlow, PyTorch, and specialized platforms like DeepMind or IBM Watson, which are used by researchers to develop and deploy AI models in scientific research. Proficiency in programming languages like Python and understanding of machine learning concepts are essential for roles in AI for science.

What are the key skills and qualifications needed to thrive as an AI for Science specialist, and why are they important?

To thrive as an AI for Science Specialist, you need a strong background in computer science, mathematics, and scientific domains, often supported by advanced degrees (e.g., PhD or MSc) in relevant fields. Proficiency with machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools, and familiarity with high-performance computing environments are typically required. Critical thinking, interdisciplinary collaboration, and effective communication are crucial soft skills for translating scientific problems into AI solutions. These skills are vital for developing innovative models, ensuring research rigor, and enabling impactful scientific discoveries.

What is the difference between Ai For Science vs Data Scientist?

AspectAi For ScienceData Scientist
Required CredentialsDegree in Science, Computer Science, or related fields; knowledge of AI and machine learningDegree in Statistics, Computer Science, or related fields; strong programming skills
Work EnvironmentResearch labs, scientific institutions, tech companies focused on scientific applicationsCorporate, tech firms, finance, healthcare, and other industries analyzing data
Industry UsageApplied to scientific research, simulations, and experimental data analysisUsed for data analysis, predictive modeling, and business insights

Ai For Science focuses on applying AI techniques to scientific research and experiments, often requiring a background in science and specialized knowledge of AI. Data Scientists analyze large datasets across various industries to extract insights and build models. While both roles involve AI and data analysis, Ai For Science is more research-oriented within scientific contexts, whereas Data Scientists work across diverse sectors on data-driven decision making.

What are popular job titles related to Ai For Science jobs in California? For Ai For Science jobs in California, the most frequently searched job titles are:
What job categories do people searching Ai For Science jobs in California look for? The top searched job categories for Ai For Science jobs in California are:
What cities in California are hiring for Ai For Science jobs? Cities in California with the most Ai For Science job openings:
Ai For Science jobs near you
Infographic showing various Ai For Science job openings in California as of August 2026, with employment types broken down into 2% Internship, 84% Full Time, 4% Part Time, and 10% Contract. Highlights an 91% In-person, 3% Hybrid, and 6% Remote job distribution.

Senior HPC Performance Engineer - AI for Science at Scale

Nvidia Corporation

Santa Clara, CA • On-site

$143K - $189K/yr

Full-time

Re-posted 29 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 242 rated software companies

Job description

NVIDIA has become the platform upon which every new AI-powered application is built. We are seeking a Sr. HPC Performance engineer to join our team of scientists and engineers passionate about building the next generation of scientific machine learning (ML) frameworks. Starting with digital biology, through high performance computing (HPC) and powerful ML methods, together, we will advance NVIDIA's capacity to accelerate AI for Science and industries that depend on it.
What you'll be doing:
  • Design and implement computationally performant features for large scale, CUDA-backed ML training frameworks, using low level acceleration and scaling strategies such as kernel design, GPU porting, data structure innovations, distributed learning technologies
  • Optimize computational performance of wide range of business-critical ML models via accelerated hardware and software stack, as well as algorithmic improvements
  • Develop and maintain HPC software stack for atomistic modeling and generative machine learning in digital biology and beyond
  • Collaborate with multiple HPC, AI infrastructure, and research teams
  • Drive the testing and maintenance of the algorithms and software modules

What we need to see:
  • Advanced degree in a quantitative field such as Computer Science, Computational Biophysics, Computational Chemistry, Physics, Mathematics, or equivalent experience
  • 5+ years of relevant experience
  • Consistent track record in performance engineering as well as software design, building and packaging and launching software products, with a focus on acceleration
  • Deep understanding of parallel programming in C++, Python; programming experience CUDA or OAI Triton
  • Fluent in modern machine learning frameworks such as PyTorch, JAX, Warp
  • Experience with HPC solutions to research problems for biology or chemistry, including but not limited to atomistic simulations
  • Recognized for technical leadership contributions, capable of self-direction, and ability to learn from and teach others
  • You should display strong communication skills, be organized and self-motivated, and play well with others (be an excellent teammate!)

Ways to stand out from the crowd:
  • Contribution to major scientific AI for Science codebase with acceleration features such as new kernels
  • Familiarity with pioneering language and geometric models used in AI for Science applications in biology and chemistry

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We are an equal opportunity employer and value diversity at our company. We have some of the most forward-thinking, resourceful and talented people in the world working with us and our engineering teams are growing fast in some of the hottest state-of-the-art fields: Digital Biology, Artificial Intelligence, and Autonomous Vehicles. Are you a creative and autonomous engineer with a real passion for machine learning, computational chemistry, data science & parallel computing? If so, 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.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until February 21, 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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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