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Generative Ai Physics Jobs in Colorado (NOW HIRING)

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Generative Ai Physics information

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.

What cities in Colorado are hiring for Generative Ai Physics jobs?

Cities in Colorado with the most Generative Ai Physics job openings:

Machine Learning Engineer

Grey Matters Defense Solutions

Centennial, CO • On-site

$154K - $195K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 5 days ago


Job description

Job Title: Machine Learning Engineer
Clearance Required: TS/SCI
Location: Centennial, CO | Hybrid
About Us
Grey Matters Defense Solutions, LLC is a specialized firm in software development, data analytics, and advanced remote sensing technologies, tailored to meet the complex demands of the defense and intelligence sectors. Our team spans senior-level experts from organizations such as the Defense Intelligence Agency (DIA), National Reconnaissance Office (NRO), Defense Advanced Research Projects Agency (DARPA), and the U.S. Armed Forces, as well as recent graduates and military veterans. By integrating the skills of subject matter experts, analysts, software engineers, and data scientists, we deliver unique artificial intelligence algorithms and applications for the defense and intelligence community.
About the Role
As a Machine Learning Engineer at Grey Matters, you will solve real-world problems relevant to the Intelligence Community (IC) and Department of Defense (DoD) using a combination of FOSS, GOTS, and COTS software and hardware. You will contribute to the full AI development lifecycle, from research and feasibility prototyping through integration, development, and product deployment.
Key Responsibilities
  • Support end-to-end model development: architecture selection, training, evaluation, and iteration against mission problems, from feasibility prototype to production candidate
  • Design and run rigorous experiments: baselines, ablations, and held-out evaluation, with clear reporting that supports program decisions
  • Package and deploy models into operational environments, and improve them through continual data acquisition
  • Collaborate with data engineers to support data selection, pre-processing, curation, and extract/transform/load (ETL) of relevant datasets for AI/ML development
Required Qualifications
  • U.S. citizenship
  • Active Top Secret security clearance (SSBI/Tier 5 investigation)
  • Bachelor's degree in a related technical field
  • 7+ years of professional experience with Python
  • 4+ years of hands-on experience with PyTorch or another ML/DL framework
  • Extensive experience training customized state-of-the-art AI models on real-world datasets
  • Strong understanding of data structures, numerical methods, and algorithm design
  • Experience developing software in a Unix/Linux environment
  • Excellent analytical and problem-solving skills
  • Ability to work under minimal supervision
  • Strong verbal and written communication skills
Preferred Qualifications
  • Knowledge of and experience with self-supervised pretraining and downstream adaptation, transfer learning, generative models, and transformers
  • Multi-GPU and distributed training experience (PyTorch DDP or FSDP), including shared cluster resources (Slurm, Kubernetes, Run:ai)
  • Experience with experiment tracking and data/model versioning for reproducibility (MLflow, Weights & Biases, DVC)
  • Experience across deep learning domains, including Natural Language Processing (NLP), computer vision, and time series data
  • Familiarity with other ML/DL frameworks and libraries (PyTorch Lightning, TensorFlow, Keras, fastai, scikit-learn, etc.)
  • Comfort working in restricted or air-gapped development environments
  • Master's or doctoral degree in Computer Science, Data Science, Mathematics, Physics, or a related field

Salary Range: $154,000 - $195,000
Grey Matters Defense Solutions, LLC offer a comprehensive benefits package including medical, dental, vision, life insurance, short-term, long-term disability, and voluntary benefits such as accident, hospital indemnity, and wellness benefits.
Additional Benefits:
  • 25% (of salary) employer contribution distributed monthly to your SEP IRA
  • Individual Benefit Account 25% (of salary to pay for medical insurance premiums and funded time off)
  • Employee assistance program
  • Employee discount
  • Health savings account
  • Referral program

Visit us at Grey Matters Defense Solutions
https://www.linkedin.com/company/grey-matters-defense-solutions/
"Know Your Rights: Workplace Discrimination is Illegal"
Questions contact: [email protected]
All qualified applicants will receive consideration for employment regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
Grey Matters Defense Solutions, LLC participates in E-Verify. Federal law requires all employers to verify the identity and employment eligibility of all persons hired to work in the United States.
Grey Matters Defense Solutions, LLC complies with the Colorado Artificial Intelligence Act (CAIA) and maintains policies, controls, and oversight practices designed to mitigate algorithmic discrimination, promote transparency, and ensure responsible use of AI systems in accordance with Colorado law.