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Remote Python Jobs in Layton, UT (NOW HIRING)

Senior Machine Learning Scientist

Salt Lake City, UT · On-site +1

$88K - $121K/yr

Salt Lake City, UT, Hybrid (3 days in office, 2 days can be remote) Benefits Eligible: Yes Manager ... Expertise in python and modern ML tooling (PyTorch preferred). Track record of taking models from ...

AI Engineer

Salt Lake City, UT · On-site +1

$101K - $159K/yr

Python (Programming Language) - Preferred * Microsoft Azure - Preferred * Human Machine Interfaces ... remote tools.. * Applicant should have experience in infrastructure disciplines of networking ...

Senior Software Engineer II

Salt Lake City, UT · On-site +1

$197K - $232K/yr

Remote Department Engineering Compensation: $197.4K - $232K • Offers Equity At Confluent, we are ... Python) and strong fundamentals in data structures, algorithms, and system design. * Hands-on ...

Senior Machine Learning Scientist

Salt Lake City, UT · On-site +1

$88K - $121K/yr

Salt Lake City, UT, Hybrid (3 days in office, 2 days can be remote) Benefits Eligible: Yes Manager ... Expertise in python and modern ML tooling (PyTorch preferred). Track record of taking models from ...

This is a remote-first role with occasional (~1x month) travel. Responsibilities and Duties ... g., Python, Power BI, Tableau, SQL) * Bonus: Experience or interest in healthcare Benefits

Proficiency with at least one modern programming language such as TypeScript, JavaScript, C#, Java, or Python. * Experience with automated testing frameworks such as Playwright, Cypress, Selenium ...

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Remote Python information

See Layton, UT salary details

$12

$53

$78

How much do remote python jobs pay per hour?

As of Jun 20, 2026, the average hourly pay for remote python in Layton, UT is $53.26, according to ZipRecruiter salary data. Most workers in this role earn between $43.89 and $60.48 per hour, depending on experience, location, and employer.

What are Remote Python jobs?

Remote Python jobs are positions where you work primarily with the Python programming language but do so from a location outside of a traditional office, such as your home or another remote location. These jobs can include roles like software developer, data analyst, backend engineer, or machine learning engineer, all of which use Python for building applications, analyzing data, or automating tasks. Remote Python jobs are popular due to Python's versatility and the growing demand for flexible work arrangements in the tech industry.

What are the key skills and qualifications needed to thrive as a Remote Python Developer, and why are they important?

To thrive as a Remote Python Developer, you need strong programming skills in Python, experience with software development life cycles, and a relevant degree or professional experience. Familiarity with tools like Git, Docker, cloud platforms (e.g., AWS), and frameworks such as Django or Flask is typically required, along with knowledge of remote collaboration tools like Slack and Jira. Excellent problem-solving abilities, self-motivation, and effective communication are crucial soft skills for remote team integration and project delivery. These skills ensure efficient, high-quality code development, seamless teamwork, and the ability to meet project goals independently in a remote environment.

What Are Remote Jobs That Use Python?

Remote jobs that use Python focus on coding software and applications to meet the needs or business objectives of your employer. This may involve working with a database, customizing an existing application, or otherwise modifying software based on its expected environment. You can also find a few remote roles that allow you to teach Python instead of using it. Many remote jobs that use Python also involve coding in other common languages as necessary—Python may be the bulk of the work, but the ability to switch to other modes of programming as needed is essential for success in this field. As a remote employee or independent contractor, you may use virtual office software to coordinate with others, upload software into a central database for testing, or work odd hours to meet the needs of your client.

What is the difference between Remote Python vs Remote Data Analyst?

AspectRemote PythonRemote Data Analyst
Required SkillsPython programming, scripting, libraries (e.g., Pandas, NumPy)Data analysis, SQL, Excel, visualization tools
CertificationsPython certifications, data science coursesData analysis certifications, SQL certifications
Work EnvironmentRemote, tech companies, startupsRemote, finance, marketing, consulting firms
Industry UsageSoftware development, automation, backend servicesBusiness intelligence, market research, reporting

Remote Python roles focus on coding, automation, and software development using Python, while Remote Data Analysts analyze data sets to generate insights. Both roles often work remotely and require analytical skills, but their core responsibilities and tools differ significantly.

How do Remote Python Developers typically collaborate and communicate with their teams?

Remote Python Developers often work closely with distributed teams using collaboration tools like Slack, Zoom, and GitHub. Clear communication and regular check-ins are essential for syncing on project requirements, code reviews, and troubleshooting. Developers are encouraged to document their code thoroughly and proactively update their progress to ensure smooth workflow across different time zones. This environment fosters independence and strong written communication skills, while also providing opportunities to participate in virtual standups, sprint planning, and peer programming sessions.
What are the most commonly searched types of Python jobs in Layton, UT? The most popular types of Python jobs in Layton, UT are:
What cities near Layton, UT are hiring for Remote Python jobs? Cities near Layton, UT with the most Remote Python job openings:
Infographic showing various Remote Python job openings in Layton, UT as of June 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 100% Remote job distribution, with an average salary of $110,784 per year, or $53.3 per hour.

Senior Machine Learning Scientist

Zanskar

Salt Lake City, UT • On-site, Remote

$88K - $121K/yr

Full-time

Posted 29 days ago


Job description

Role Overview 
Title: Senior Machine Learning Scientist (Surrogate modeling & decision science in the earth sciences)
Hours: Full-Time, Salaried
Location: Salt Lake City, UT, Hybrid (3 days in office, 2 days can be remote)
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 building technology to find and develop new geothermal resources in order to make geothermal a cheap and vital contributor to a carbon-free electrical grid.
 
To do that, we combine deep subsurface expertise with advanced AI technologies—including modern machine learning, scalable scientific computing, and uncertainty-aware modeling—to dramatically improve geothermal discovery and development outcomes. We build systems that can learn from sparse and noisy data, emulate expensive physics simulations, and help teams make faster, higher-confidence decisions about where to drill and how to develop fields.
 
Who you are
You will help build the modeling and decision-making core of Zanskar’s geothermal exploration software. This role blends scientific machine learning (surrogate modeling) with sequential decision-making under uncertainty. A successful candidate will:
Explore: you’re open-minded about methods and will prototype, benchmark, and iterate across approaches.
Reproduce & adapt: you can implement ideas from papers and new frameworks quickly, then harden the best ones into reliable workflows.
Decision-minded: you care about end-to-end outcomes (value, risk, time-to-decision), not just model accuracy.
Uncertainty-first: you build models that are accurate, well-calibrated, and dependable under distribution shift and sparse data regimes.
Collaborative: you work well with domain experts and can translate between geology/engineering intuition and ML systems.
 
What you’ll do
Build fast, reliable models that emulate or augment computationally expensive physics-based simulations (e.g., reservoir, wellbore, and coupled multi-physics workflows).
Evaluate and compare multiple modeling approaches (physics-informed, operator learning, transformers, diffusion models, etc.), establishing strong baselines and selecting methods based on evidence.
Build multi-step decision systems for exploration and appraisal: POMDP-style planning and belief-space decision making to recommend exploration steps.
Translate scientific and engineering questions into well-defined learning and decision problems: inputs/outputs, constraints, boundary/initial conditions, reward/cost structure, and success metrics (e.g., expected NPV, probability of success, downside risk).
Prototype, benchmark, and iterate across approaches (POMDP solvers, RL methods, VOI-style baselines, MPC-style replanning), then harden the best ones into reliable workflows and APIs.
Collaborate deeply with geoscientists, reservoir engineers, and software engineers to integrate these models and policies into production software.
 
What we’re looking for
3+ years of applied ML experience, ideally in scientific ML, decision-making under uncertainty, surrogate modeling, robotics/control, or related engineering/science domains.
Expertise in python and modern ML tooling (PyTorch preferred).
Track record of taking models from prototype → rigorous evaluation → adoption by technical stakeholders.
Strong fundamentals in probability/statistics and comfort with messy, real-world scientific datasets.
Experience building or using surrogate models for expensive simulators (PDE-driven systems, multi-physics, or similar).
Relevant technical strengths
Surrogate modeling. 
Sequential decision-making under uncertainty and reinforcement learning. 
Software engineering: Git, code review, reproducibility, CI basics, Docker/container workflows.
Experience with diffusion models.
Exposure to subsurface modeling domains: geothermal, oil & gas, CCS, hydrogeology, geoscience, or related.
Familiarity with cloud infrastructure and data systems (SQL, object storage, orchestration).
 
Location and Benefits
This position is based out of our headquarters in Salt Lake City, Utah, and is hybrid.
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.