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Physics Informed Machine Learning Jobs in Kentucky

Bachelor's, Master's, or PhD in Computer Science, Statistics, Mathematics, Physics, or another quantitative discipline. * Demonstrated success developing and deploying production machine learning ...

Bachelor's, Master's, or PhD in Computer Science, Statistics, Mathematics, Physics, or another quantitative discipline. * Demonstrated success developing and deploying production machine learning ...

... Physics, Industrial Engineering, Mechanical Engineering, or Robotics) * Ability to take an ... Machine learning data set design or optimization * Dynamic system modeling and control * The desire ...

You'll collaborate closely with machine learning experts and cross-functional teams, rapidly iterating over new ideas, and leveraging user behavior data to make informed decisions. Your challenge ...

$175K - $308K/yr

PhD in computer science, statistics, physics, chemistry, electrical engineering, or operations research. Other hard sciences may also be considered. * 3 publications in top-tier machine learning ...

$36K - $49K/yr

PhD in Physics, Astronomy or a related field by date of appointment * The applicants must demonstrate strong expertise in artificial intelligence, machine learning, and image processing Preferred ...

Specialized Analytics Senior Analyst

Florence, KY · On-site

$85K - $107K/yr

... informed about business and technology shifts, identifying both potential and existing fraud ... Build predictive models and machine-learning and AI algorithms with large amounts of structured and ...

$184K - $324K/yr

Experience with a wide range of physics simulation software and their contact mechanics (e.g. Mujoco, IssacLab simulator, Drake, etc.). * Successful record of employing machine learning techniques to ...

... Machine Learning (ML) and AI to simulation solutions are key to success. The team consists of world‑class experts in solidification physics, casting, metallurgy, and simulation. Experience with ...

Bachelor's degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding. * Experience designing ...

... machine learning. We welcome candidates who will enrich our active and intellectually diverse ... D. in Physics or a closely related field. The application must include a cover letter summarizing ...

$350K - $475K/yr

Bachelor's degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding. * Clarity in ...

This individual combines expertise in computational modeling, applied mathematics, physics, and data science to ensure that machine learning models, agent-based simulations, and analytical frameworks ...

This role sits at the intersection of software engineering, machine learning, and RF physics, perfect for a developer who wants to get close to the hardware. Responsibilities: * End-to-End ML ...

Make informed recommendations regarding competing technical solutions by maintaining awareness of ... Relevant experience must be in designing/implementing machine learning, data science, advanced ...

$145K/yr

... machine learning or related area * BS/MS/PhD degree in a technical field - Engineering, Computer Science, Math, Physics, or similar * Proven research background in academic or professional ...

$350K - $475K/yr

Bachelor's degree or equivalent experience in computer science, electrical engineering, statistics, machine learning, physics, robotics, or similar. * Strong engineering skills, ability to contribute ...

As an Artificial Intelligence/Machine Learning Engineer with Wyetech, you will work directly with ... Your work will streamline analytical tasks, improve data accessibility, and support rapid, informed ...

Apply probability theory, statistical analysis, and machine learning techniques to build robust ... PhDs graduating by Summer 2026 or postdocs in quantitative fields such as mathematics, physics ...

Showing results 41-60

Physics Informed Machine Learning information

What is a physics informed machine learning?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What are the typical challenges faced by professionals working in physics informed machine learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.

What are the key skills and qualifications needed to thrive in the physics informed machine learning position, and why are they important?

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are popular job titles related to Physics Informed Machine Learning jobs in Kentucky?

For Physics Informed Machine Learning jobs in Kentucky, the most frequently searched job titles are:

What job categories do people searching Physics Informed Machine Learning jobs in Kentucky look for?

The top searched job categories for Physics Informed Machine Learning jobs in Kentucky are:

What cities in Kentucky are hiring for Physics Informed Machine Learning jobs?

Cities in Kentucky with the most Physics Informed Machine Learning job openings:

Infographic showing various Physics Informed Machine Learning job openings in Kentucky as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 73% Full Time, 22% Part Time, and 3% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution.

Head of Applied Machine Learning - Application Fraud

On-site

SentiLink Corp
Software Development • 11 - 50 employees

Other

Medical, Retirement, PTO

Posted 18 days ago


Job description

SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transact with confidence. We’re building the future of identity verification in the United States replacing a clunky, ineffective, and expensive status quo with solutions that are 10x faster, smarter, and more accurate.

We’ve seen tremendous traction and are growing extremely quickly. Our real-time APIs have helped verify hundreds of millions of identities, starting with financial services and rapidly expanding into new markets. SentiLink is backed by world-class investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.

We’ve earned recognition from TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, American Banker, LendIt, and have been named to the Forbes Fintech 50. We have also been named a 2026 FICO Industry Vanguard Decision Award Winner. Last but not least, we’ve even made history - we were the first company to go live with the eCBSV and testified before the United States House of Representatives on the future of identity.

SentiLink supports a variety of ways to work, ranging from fully remote to in-office. We operate as a digital-first company with strong collaboration across the U.S. and India. We maintain physical offices in Austin, San Francisco, New York City, Seattle (Bellevue), Los Angeles, and Chicago in the U.S., and in Gurugram (Delhi) and Bengaluru in India. If you’re located near one of these offices, we would love for you to spend time in the office regularly. Some roles are hybrid or in-office by design. For example, our engineering team in India works primarily from our Gurugram office.

Role:

SentiLink builds the fraud detection and identity verification models much of the US financial system runs on. As Head of Applied ML, you own a major ML domain end to end.

You’ll lead a team of 4 applied ML scientists, 6 by the end of 2026, all experienced and technically deep enough to challenge you daily. This is a people management role that stays close to the work. Technical credibility is non-negotiable: you’ll review PRs, push on modeling decisions, and unblock the team.

Data science drives product decisions here, and we expect you to become a strategic leader in both the product and ML domains you own. We use AI across all of our work, are exploring where it belongs in the products themselves, and hold a hard line on AI safety and data governance.

Technologies: Python 3, PostgreSQL, AWS, XGBoost, scikit-learn, pandas, Elasticsearch and OpenSearch, Neo4j, MLflow, Flyte, and use of modern LLM tooling.

Responsibilities:
  • Directly manage a team of applied ML scientists, 4 today and growing to 6 by the end of 2026, and set the engineering and modeling practices they work by.

  • Own strategy and execution for your applied ML domain: roadmap, priorities, resourcing, and results.

  • Act as a technical mentor who can dive deep and give specific, useful direction. Guide modeling and architecture decisions, review PRs, and stay current on the codebase and production systems.

  • Partner with senior leadership, Product, Engineering, and Risk to set priorities and deliver on aggressive timelines.

  • Represent your domain in product strategy discussions and help shape where those products go next.

  • Own SentiLink’s fraud detection and identity models across the full lifecycle: data acquisition, feature engineering, labeling strategy, model training, experimentation, production deployment, monitoring, and iteration.

  • Research emerging fraud patterns, build new ML capabilities for identity verification and financial risk, and design analyses that inform product and business decisions.

  • Drive how the team uses AI in its own work, keep pushing the boundary on what that unlocks, and help define where AI belongs in our products.

Requirements:
  • 10+ years of industry experience applying machine learning or statistics to real-world problems, or 7+ years with a relevant PhD, including 6+ years directly managing machine learning or data science teams across two companies or more. Startup experience strongly preferred.

  • Experience leading ML or data science teams in fraud, identity, fintech, banking, financial services, payments, or adjacent risk-focused domains. Strongly desired, but not strictly required.

  • Bachelor’s, Master’s, or PhD in Computer Science, Statistics, Mathematics, Physics, or another quantitative discipline.

  • Demonstrated success developing and deploying production machine learning models, plus experience writing production-quality Python code and tests.

  • Strong practical ML and applied statistics knowledge: able to scope solutions quickly with standard tooling and go deep where it pays off.

  • Very strong end to end, with a track record of owning a technical domain and driving it to measurable business impact: planning, defining success criteria, getting buy-in, building the solution, and delivering it, whether in production, in a deck, or as strategy.

  • Fluent with modern LLMs and AI-assisted development workflows, and opinionated about where they help and where they don’t. Sound judgment when working with sensitive data under real information security and data governance constraints.

  • Excellent communicator, including with senior leadership and cross-functional stakeholders. Detail oriented and thoughtful, someone we can rely on to make business-changing decisions while thriving on varied, open-ended, high-impact problems.

  • Candidates must be legally authorized to work in the United States and must live in the United States.

Compensation:

$210,000-$260,000/year + equity + benefits

Perks:
  • Employer paid group health insurance for you and your dependents

  • 401(k) plan with employer match (or equivalent for non US-based roles)

  • Flexible paid time off

  • Regular company-wide in-person events

  • Home office stipend, and more!

Corporate Values:
  • Follow Through

  • Deep Understanding

  • Whatever It Takes

  • Do Something Smart

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