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Generative Ai Physics Jobs (NOW HIRING)

Stardock Corporation

Senior Game Developer

Plymouth, MI · On-site

$120K - $160K/yr

Optimization, networking, UI/UX, AI, generative AI, physics, data management, graphics, gameplay, audio, HLSL/GLSL shaders, pipelines, terrain. * Able to learn new technology quickly and execute on a ...

Stardock Corporation

Senior Game Developer

Plymouth, MI · On-site

$120K - $160K/yr

Optimization, networking, UI/UX, AI, generative AI, physics, data management, graphics, gameplay, audio, HLSL/GLSL shaders, pipelines, terrain. * Able to learn new technology quickly and execute on a ...

Kanak Elite Services Inc

AI Engineer

Santa Clara, CA · On-site

We are seeking a Generative AI (GenAI) Design Engineer to join our team and drive innovation in AI ... Create high-fidelity digital twins combining physics-based solvers (CFD, plasma, heat transfer ...

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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 Sep 2, 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 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.

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 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.

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Generative Ai Physics jobs near you
Infographic showing various Generative Ai Physics job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $61,160 per year, or $29.4 per hour.

ML Research Scientist, Foundation Models (Senior / Staff / Principal)

Genesis Molecular AI

San Mateo, CA • On-site

$112K - $143K/yr

Full-time

Re-posted 9 days ago

Job description

Job Summary:
Genesis Molecular AI is pioneering foundation models for molecular AI to unlock a new era of drug design and development. As a key member of the Genesis AI team, you will lead critical research initiatives in generative AI and collaborate with multidisciplinary researchers to create groundbreaking models that impact drug discovery.
Responsibilities:
• Lead transformative research projects from conception to implementation, tackling core challenges in generative modeling for molecular systems.
• Design and develop novel models and algorithms, building upon the latest literature in diffusion models, flow matching, RL, LLMs, and other cutting-edge areas.
• Execute ambitious experiments at scale, leveraging our world-class computational infrastructure to rigorously validate your hypotheses and push the boundaries of the state-of-the-art.
• Collaborate intensely with a multidisciplinary team to translate your research into tangible impact on our drug discovery platform.
• Contribute to the global research community by publishing some of your work and representing Genesis at top tier AI/ML conferences and workshops.
• Mentor and guide other researchers and engineers, fostering a culture of shared learning, growth, and innovation.
Qualifications:
Required:
• A deep learning expert with a portfolio of novel research in one or more cutting-edge domains of generative or predictive modeling (e.g., diffusion, flow matching, RL, foundation model architectures and training methods).
• An independent, first-principles thinker with a strong sense of ownership over your research projects and a drive to see them through to completion.
• A strong coder, comfortable with going deep into the engineering stack to build, debug, and ship your own models.
• A curious, problem-oriented mind, excited to dive into the emerging field at the intersection of AI, physics, chemistry, and biology and make foundational contributions and discoveries. No prior experience in biology or chemistry is necessary – only willingness to learn.
• A true team player with strong communication skills who thrives in highly collaborative, mission-driven environments where science and engineering are deeply intertwined.
• Inspired by our culture of intellectual curiosity and the shared belief that breakthroughs happen when diverse perspectives and minds unite.
Preferred:
• PhD in machine learning, computer science, other computational sciences or equivalent research experience, demonstrated by a strong publication record.
• Hands-on experience with Pytorch, Pytorch Lightning, Ray Distributed Training, Pytorch Geometric, etc.
• Experience in distributed training and inference of large models on GPU clusters.
• Familiarity with molecular data, (proteins, small molecules), physics-informed ML, or 3D point cloud data.
Company:
Genesis Therapeutics unifies AI and biotech to accelerate the discovery of new medicines. Founded in 2019, the company is headquartered in South San Francisco, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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