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Physics Informed Machine Learning Jobs in Utah (NOW HIRING)

Zanskar

Senior Distributed Systems Engineer

Salt Lake City, UT · On-site

$101K - $138K/yr

... machine learning modeling. Who you are The Senior Distributed Systems Engineer will play a critical role developing and maintaining Zanskar's next-generation multi-physics well-targeting engine. A ...

Zanskar

Senior/Staff Software Engineer

Salt Lake City, UT · On-site

$118K - $156K/yr

... machine learning modeling. Who you are The Senior/Staff Software Engineer will play a critical role developing and maintaining Zanskar's next-generation multi-physics well-targeting engine. A ...

Zanskar

Senior Distributed Systems Engineer

Salt Lake City, UT · Hybrid

$101K - $138K/yr

... machine learning modeling. Who you are The Senior Distributed Systems Engineer will play a critical role developing and maintaining Zanskar's next-generation multi-physics well-targeting engine. A ...

Zanskar

Senior/Staff Software Engineer

Salt Lake City, UT · On-site

$118K - $156K/yr

... machine learning modeling. Who you are The Senior/Staff Software Engineer will play a critical role developing and maintaining Zanskar's next-generation multi-physics well-targeting engine. A ...

Zanskar

Senior Distributed Systems Engineer

Salt Lake City, UT · Hybrid

$101K - $138K/yr

... machine learning modeling. Who you are The Senior Distributed Systems Engineer will play a critical role developing and maintaining Zanskar's next-generation multi-physics well-targeting engine. A ...

Pwc

US Tech - AI Engineering Manager

Salt Lake City, UT · On-site

$73K - $244K/yr

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

Pwc

NGA AI Engineer Manager

Salt Lake City, UT · On-site

$73K - $244K/yr

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

ARUP

Technologist, Trainee

Salt Lake City, UT · On-site

$21.94/hr

... machinery, etc. Communicate: Frequently communicate with others. PPE: Biohazard laboratory ... Chemistry * 23 semester credit hours of science courses * 3 semester credit hours of physics, math ...

Integrated Power Services

Manual Machinist

Price, UT · On-site

$20 - $27/hr

Why IPS? If you're searching for a place where you can grow, continue learning, and make a ... You will use a variety of manual machine tools and balancing equipment for rotating machinery ...

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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 Utah?

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

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

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

Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in Utah as of August 2026, with employment types broken down into 6% Internship, 37% Full Time, 51% Part Time, and 6% Contract. Highlights an 100% In-person job distribution.

Senior/Staff Backend Engineer

Salt Lake City, UT • Hybrid

Zanskar
Clean Energy Power Generation • 11 - 50 employees
Learn more about Zanskarexternal

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 7 days ago

Job description

Senior/Staff Backend Engineer   Role Overview 

Title:Senior/Staff Backend Engineer 

Hours: Full-Time, Salaried

Location: Salt Lake City, UT, Hybrid

Benefits Eligible: Yes

Manager: Head of Reservoir R&D

Why we exist

Geothermal energy is the most abundant renewable energy source in the world. There is 2,300 times more energy in geothermal heat in the ground than in oil, gas, coal, and methane combined. However, historically it's been hard to find and expensive to develop. At Zanskar, we're using better technology to find and develop new geothermal resources in order to make geothermal a cheap and vital contributor to a carbon-free electrical grid. We are revolutionizing the exploration process, setting new industry standards for discovery rates and finding new prospects at an unprecedented scale. To reduce risk and improve outcomes, we rely on novel software and machine learning modeling.

Who you are

The Senior/Staff Backend Engineer will play a critical role developing and maintaining Zanskar's next-generation multi-physics well-targeting engine. A successful candidate will:

  • Lead - you will be a trusted leader who can both design and deliver a reliable distributed compute system that meets the ongoing needs of our scientific research teams.
  • Learn - you will be entering a team with an existing system in place that needs to grow and scale. You will learn the domain from your peers as you identify how to migrate the system for scale and reliability.
  • Collaborate - you won't just be working with people like yourself. You'll be working with some of the most brilliant geophysicists, geoscientists, seismologists and engineers tackling the challenges of geothermal discovery. Collaborating with your peers to solve hard problems is the name of the game.
  • Teach - you will bring critical skills and experience that should be taught to others. You will have the opportunity (and education) to help others better understand your craft as a distributed systems engineer, while you learn from them their craft in modeling the earth's subsurface.
What we're looking for
  • Minimum 7+ years experience in software engineering in a business environment, ideally with a heavy scientific component.
  • Experience leading the design and implementation of distributed computing systems.
  • Proven technical skills:
    • Experience with the development of fault-tolerant, resilient event-driven architectures, and building and managing orchestration systems to massively scale cloud-based workloads (serverless, Kubernetes, and/or custom VM fleets).
    • Experience defining and developing persistent data storage for digital artifacts, both with RDBMS and cloud blob storage at scale.
    • Experience ensuring system observability through logging, monitoring, alerting and metrics.
    • Familiarity with software engineering best practices: CI/CD (GitHub Actions or similar), version control (GitHub), containerization (Docker) and Infrastructure as Code (Terraform, Pulumi).
    • Experience architecting, permissioning and maintaining cloud resources (GCP, AWS).
    • Fluency in Python and SQL are required.
    • Experience with any of the following is a plus: experiment tracking, optimization methods, applied algorithm development, reinforcement learning and other AI/ML techniques, web development, and familiarity with geoscience concepts and applications.
Location and Benefits
  • The position is based out of our headquarters in Salt Lake City, Utah, and is a hybrid position
  • Benefits include:
    • Paid holidays
    • 15 days PTO + PTO accrual increase based on tenure
    • Medical, dental and vision coverage
    • 401k
    • Stock options
    • Growth opportunities at a company with a direct impact in displacing carbon emissions
Equal Opportunity Employer

Zanskar is an equal-opportunity employer and complies with all applicable federal, state, and local fair employment practice laws.

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