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Generative Ai Physics Jobs (NOW HIRING)

Nvidia

OR · On-site

You should be comfortable working in a dynamic environment, and have experience with Generative AI ... Physics, Mathematics, other Engineering or related fields (or equivalent experience) * 8+ years of ...

Nvidia

You should be comfortable working in a dynamic environment, and have experience with Generative AI ... Physics, Mathematics, other Engineering or related fields (or equivalent experience) * 8+ years of ...

Pravāh

AI Weather Scientist

San Francisco, CA · On-site

$150K - $250K/yr

Assess the applicability of state-of-the-art AI methodologies including foundation models, generative architectures, and physics-informed ML to weather and climate forecasting. * Work at the ...

Photon

GenAI Solution Architect - VA

Norfolk, VA

$61 - $80.25/hr

We are seeking an AI Engineer to work on a Generative AI initiative to join our team. The ideal ... Bachelor's or master's degree in computer science, Data Science, Statistics, Math, Physics, or ...

Photon

GenAI Solution Architect - VA

Norfolk, VA · On-site

$61 - $80.25/hr

We are seeking an AI Engineer to work on a Generative AI initiative to join our team. The ideal ... Bachelor's or master's degree in computer science, Data Science, Statistics, Math, Physics, or ...

Vrtx

Principal Data Scientist, Digital & AI

Boston, MA · Hybrid

$152K - $228K/yr

... physics, epidemiology, health economics * 5+ years of experience developing data science solutions in an industry or academic context, with 2+ years of experience integrating generative AI methods ...

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Generative Ai Physics information

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$11K

$61.2K

$94.5K

How much do generative ai physics jobs pay per year?

As of Jun 12, 2026, the average yearly pay for generative ai physics in the United States is $61,160.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,000.00 and $64,500.00 per year, depending on experience, location, and employer.

What is the difference between Generative Ai Physics vs Data Scientist?

AspectGenerative Ai PhysicsData Scientist
Required CredentialsPhysics degree, AI/ML knowledgeStatistics, Computer Science, Data Analysis
Work EnvironmentResearch labs, tech companies, academiaBusiness, tech firms, consulting
Industry UsagePhysics simulations, AI model developmentData analysis, predictive modeling
Common Search IntentUnderstanding AI in physics researchAnalyzing data trends, insights

Generative Ai Physics focuses on applying AI techniques to physics problems, often involving simulations and model development. Data Scientists analyze data to extract insights across various industries. While both roles require analytical skills, Generative Ai Physics emphasizes physics knowledge combined with AI expertise, whereas Data Scientists focus on data analysis and interpretation.

What are the key skills and qualifications needed to thrive as a Generative AI Physics Specialist, and why are they important?

To thrive as a Generative AI Physics Specialist, you need a solid background in physics, mathematics, and computer science, often with an advanced degree such as a Master's or Ph.D. in a related field. Expertise in machine learning frameworks (like TensorFlow or PyTorch), programming languages (such as Python), and familiarity with computational physics tools are typically required. Strong analytical thinking, creativity, and clear communication skills help in developing innovative AI models and collaborating with interdisciplinary teams. These skills enable the successful integration of AI techniques with physical systems, driving progress in research and practical applications.

What is a Generative AI Physicist?

A Generative AI Physicist is a professional who applies generative artificial intelligence techniques to solve complex problems in physics. They use models such as neural networks and deep learning algorithms to simulate, predict, or generate new physical phenomena and data. This role often involves interdisciplinary work combining expertise in physics, machine learning, and computer science. Generative AI Physicists contribute to advancements in scientific research, material discovery, and the automation of experimental design.

How does a Generative AI Physics specialist typically collaborate with other departments in interdisciplinary research projects?

As a Generative AI Physics specialist, you will often work closely with data scientists, software engineers, and domain experts from various fields such as materials science, engineering, or biomedical research. Effective collaboration involves translating complex physical models into machine learning frameworks, sharing insights to refine algorithms, and integrating AI-generated results into broader research initiatives. Regular interdisciplinary meetings and shared project management tools are commonly used to ensure alignment and foster innovation. This collaborative environment not only broadens your technical skills but also enhances your ability to communicate complex concepts to diverse teams.
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What cities are hiring for Generative Ai Physics jobs? Cities with the most Generative Ai Physics job openings:
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What job categories do people searching Generative Ai Physics jobs look for? The top searched job categories for Generative Ai Physics jobs are:
Generative Ai Physics jobs near you
Infographic showing various Generative Ai Physics job openings in the United States as of June 2026, with employment types broken down into 69% Full Time, 27% Part Time, 2% Temporary, and 2% Contract. Highlights an 73% Physical, 2% Hybrid, and 25% Remote job distribution, with an average salary of $61,160 per year, or $29.4 per hour.
Senior Solutions Architect, Generative AI Deployment and AIOps

Senior Solutions Architect, Generative AI Deployment and AIOps

Nvidia

OR • On-site

Full-time

Posted 6 days ago

Job description

NVIDIA is seeking outstanding AI Solutions Architects to assist and support customers that are building solutions with our newest AI technology. At NVIDIA, our solutions architects work across different teams and enjoy helping customers with the latest Accelerated Computing and Deep Learning software and hardware platforms. We're looking to grow our company, and build our teams with the smartest people in the world. Would you like to join us at the forefront of technological advancement? You will become a trusted technical advisor with our customers and work on exciting projects and proof-of-concepts focused on inference for Generative AI and Large Language Models (LLMs). You will also collaborate with a diverse set of internal teams on performance analysis and modeling of inference software. You should be comfortable working in a dynamic environment, and have experience with Generative AI, LLMs and GPU technologies. This role is an excellent opportunity to work in an interdisciplinary team at NVIDIA!

What You Will Be Doing:

  • Partnering with other solution architects, engineering, product and business teams. Understanding their strategies and technical needs and helping define high-value solutions

  • Dynamically engaging with developers, scientific researchers, and data scientists, gaining experience across a range of technical areas

  • Strategically partnering with lighthouse customers and industry-specific solution partners targeting our computing platform

  • Working closely with customers to help them adopt and build creative solutions using NVIDIA technology and MLOps solutions

  • Analyzing performance and power efficiency of AI inference workloads on Kubernetes

  • Some travel to conferences and customers may be required (20%)

What We Need To See:

  • BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience)

  • 8+ years of hands-on experience with Deep Learning frameworks such as PyTorch and TensorFlow

  • Strong fundamentals in programming, optimizations, and software design, especially in Python

  • Proficiency in problem-solving and debugging skills in GPU orchestration and Multi-Instance GPU (MIG) management within Kubernetes environments

  • Experience with containerization and orchestration technologies, monitoring, and observability solutions for AI deployments

  • Excellent knowledge of the theory and practice of LLM and DL inference

  • Excellent presentation, communication and collaboration skills

Ways To Stand Out From The Crowd:

  • Prior experience with DL training at scale, deploying or optimizing DL inference in production

  • Experience with NVIDIA GPUs and software libraries such as NVIDIA NIM, Dynamo, TensorRT, TensorRT-LLM

  • Excellent C/C++ programming skills, including debugging, profiling, code optimization, performance analysis, and test design

  • Familiarity with parallel programming and distributed computing platforms

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 April 10, 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 logo

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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