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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

$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 Jul 3, 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.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior researcher, AI director, or executive role, often requiring advanced skills in machine learning, deep learning, and data science. These roles usually involve leadership, strategic planning, and extensive experience, and they may be found in large tech companies or specialized AI firms. Compensation at this level reflects significant expertise and responsibility in developing or managing AI systems and projects.

What jobs can you get with a generative AI certification?

A generative AI certification can qualify you for roles such as AI engineer, machine learning engineer, data scientist, or research scientist, where skills in AI model development, programming, and data analysis are essential. These positions often involve developing and deploying AI models, working with tools like Python and TensorFlow, and require a strong understanding of machine learning concepts.

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.

Which 3 jobs will survive AI?

Generative AI Physics professionals, data scientists, and AI ethics specialists are likely to remain in demand as their roles require complex problem-solving, domain expertise, and ethical oversight that are difficult for AI to fully replicate. These jobs involve critical thinking, creativity, and nuanced understanding of physics and AI applications. Skills in programming, machine learning, and domain-specific knowledge will enhance job security in these fields.

What is the highest paid physics job?

In the field of physics, roles such as physics research director, senior data scientist specializing in physics-based models, or physics consultant in industries like aerospace, defense, and technology tend to have the highest salaries. These positions often require advanced degrees, specialized skills in computational modeling or AI, and extensive experience, with salaries reaching into the high six or seven figures annually.
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What cities are hiring for Generative Ai Physics jobs? Cities with the most Generative Ai Physics job openings:
What states have the most Generative Ai Physics jobs? States with the most job openings for Generative Ai Physics jobs include:
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 57% Full Time, 15% Part Time, 2% Temporary, and 26% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $61,160 per year, or $29.4 per hour.
AI Research Scientist --Generative AI for Materials Discovery

AI Research Scientist --Generative AI for Materials Discovery

Meta

Redmond, WA

$154K/yr

Full-time

Posted 17 days ago

Meta rating

7.5

Company rating: 7.5 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

130th of 202 rated software companies

Job description

Meta’s Reality Labs Research (RL-R) brings together a team of researchers, developers, and engineers to create the future of Mixed Reality (MR), Augmented Reality (AR), and Wearable Artificial Intelligence (AI). The Materials and Systems Innovation (MSI) group within Reality Labs Research creates and accelerates breakthrough materials and device technologies that unblock the path to low-cost, all-day wearable AR devices and advanced sensing and actuating systems for robotics. We identify key technology gaps requiring step-change innovation, build AI-driven autonomous discovery pipelines to compress development timelines, leverage external partners to accelerate research, and deliver high-quality technology solutions through cross-functional, high-performing teams.In this role, you will pioneer the application of generative AI to design novel compounds and molecular crystals, directly accelerating the discovery of next-generation materials for AR/VR devices and advanced robotic systems. Working at the frontier of deep generative modeling, computational chemistry, and agentic AI, you will develop and deploy state-of-the-art models — including diffusion models, flow matching, and transformer-based architectures — that predict and generate stable crystal structures and molecular candidates with target properties. Your work will be tightly integrated into our AI-driven autonomous discovery platform, collaborating with computational chemists and AI agent scientists to close the loop from molecular design to experimental validation.Together, we are going to build advanced prototypes, technologies, and toolsets that can advance how people interact with their surroundings. We invite you to join us as we work to bring these technologies from research to reality.
AI Research Scientist —Generative AI for Materials Discovery Responsibilities:
  • Develop, train, and deploy generative models (diffusion models, flow matching, variational autoencoders, transformer-based architectures) for molecular and crystal structure generation, property-conditioned design, and crystal structure prediction (CSP)
  • Design and implement reinforcement learning and alignment strategies (e.g., physics-informed reward signals from machine-learned interatomic potentials) to steer generative models toward physically stable and synthesizable candidates
  • Build foundational models and scalable pretraining pipelines that unify generative and predictive learning across molecules and crystalline materials, handling both discrete atom types and continuous 3D geometries
  • Collaborate closely with computational chemists to integrate first-principles calculations (DFT, force fields), molecular dynamics simulations, and domain-specific constraints into generative workflows
  • Partner with AI agent scientists to embed generative molecular design capabilities into LLM-based multi-agent systems, enabling closed-loop autonomous experiment planning, candidate generation, and decision making
  • Curate, preprocess, and manage large-scale molecular and crystal structure datasets for model training and benchmarking
  • Establish rigorous evaluation frameworks — measuring validity, novelty, uniqueness, stability, and synthesizability of generated structures — and benchmark against state-of-the-art methods
  • Contribute to the architecture and roadmap of the autonomous materials-discovery platform, ensuring generative design modules interface seamlessly with robotic workcells, characterization instruments, and data infrastructure

Minimum Qualifications:
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • Ph.D. degree in Machine Learning, Computational Chemistry, Materials Science, Chemical Engineering, Physics, or a closely related technical field
  • 3+ years of research experience in generative modeling applied to molecular systems, crystal structures, or materials science (academic or industry)
  • Familiarity with large-scale molecular and crystal databases and data processing pipelines for chemical data
  • Demonstrated expertise in deep generative models — including diffusion models, flow matching / continuous normalizing flows, variational autoencoders, or autoregressive models — with applications to 3D molecular or crystal structure generation
  • Programming proficiency in Python with hands-on experience in PyTorch or JAX
  • proficiency in building, training, and evaluating large-scale deep learning models
  • Track record of first-author publications in top-tier ML or computational chemistry venues (e.g., NeurIPS, ICML, ICLR, JACS, Nature Computational Science, Digital Discovery)
  • Solid understanding of crystallography fundamentals— and molecular representations (molecular graphs, SMILES, 3D conformers)

Preferred Qualifications:
  • Experience integrating ML models into agentic AI frameworks or LLM-based multi-agent systems for autonomous scientific discovery
  • Hands-on experience with computational chemistry tools and simulation frameworks (DFT codes such as VASP/Gaussian, molecular dynamics with LAMMPS/OpenMM/ASE, force field development)
  • Experience with crystal structure prediction (CSP) pipelines, including lattice energy ranking and structure relaxation using machine-learned interatomic potentials
  • Demonstrated ability to collaborate across disciplines — bridging ML research with experimental chemistry, materials science, and software engineering teams
  • Experience building or fine-tuning foundation models (100M+ parameters) for chemical or materials domains, including multimodal architectures that jointly handle molecular graphs, 3D coordinates, and periodic lattice structures
  • Knowledge of geometric deep learning, equivariant neural networks, or graph neural networks for molecular property prediction
  • Familiarity with reinforcement learning or RLHF-style alignment techniques applied to molecular or materials generation

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$154,000/year to $217,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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