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Remote Gps Machine Control Jobs in Utah (NOW HIRING)

Zanskar

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 ... control, or related engineering/science domains. Expertise in python and modern ML tooling (PyTorch ...

Zanskar

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 ... control, or related engineering/science domains. Expertise in python and modern ML tooling (PyTorch ...

BambooHR

Staff Software Engineer

Draper, UT · Remote

This is a remote position available in the state listed on this job. Additionally, employment with ... Partner with product and platform teams to translate domain-specific access control requirements ...

Cricut

Senior Accountant

South Jordan, UT · Remote

$70K - $88K/yr

Our smart cutting machines, design apps, and materials make creativity easy and accessible for ... This role will also provide leadership and oversight for a remote accounting team of four based in ...

Cricut

Senior Accountant

South Jordan, UT · Remote

$70K - $88K/yr

Our smart cutting machines, design apps, and materials make creativity easy and accessible for ... This role will also provide leadership and oversight for a remote accounting team of four based in ...

Consor Engineers

Transportation Engineer

Draper, UT · On-site +1

$100/hr

Own scope/schedule/budget, and perform QA/QC reviews of design calculations and plan sheets ... copy machines. May require occasional exposure to work environments that may include inclement ...

Consor Engineers

Transportation Engineer

Draper, UT · On-site +1

$100/hr

Own scope/schedule/budget, and perform QA/QC reviews of design calculations and plan sheets ... copy machines. May require occasional exposure to work environments that may include inclement ...

All JobsRemote Gps Machine Control JobsRemote Gps Machine Control Jobs in Utah

Remote Gps Machine Control information

What is the difference between Remote Gps Machine Control vs Remote Gps Machine Operator?

AspectRemote Gps Machine ControlRemote Gps Machine Operator
CredentialsTypically requires GPS technology training, certifications in machine control systemsRequires operator certifications, equipment operation training
Work EnvironmentOffice-based or remote monitoring, overseeing multiple machinesOn-site or remote operation of machinery in construction or surveying sites
Industry UsageUsed by project managers, engineers, and control specialistsUsed by machine operators in construction, mining, or surveying

Remote Gps Machine Control involves overseeing and managing GPS-guided machinery remotely, focusing on system setup and monitoring. In contrast, Remote Gps Machine Operator directly controls and operates machinery, often on-site or remotely, but with hands-on responsibilities. Both roles require GPS and machinery knowledge but differ in their focus on control versus management.

What are the most commonly searched types of Gps Machine Control jobs in Utah? The most popular types of Gps Machine Control jobs in Utah are:
What are popular job titles related to Remote Gps Machine Control jobs in Utah? For Remote Gps Machine Control jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Remote Gps Machine Control jobs in Utah look for? The top searched job categories for Remote Gps Machine Control jobs in Utah are:
What cities in Utah are hiring for Remote Gps Machine Control jobs? Cities in Utah with the most Remote Gps Machine Control job openings:
Remote Gps Machine Control jobs near you
Infographic showing various Remote Gps Machine Control job openings in Utah as of June 2026, with employment types broken down into 83% Full Time, 8% Part Time, 1% Temporary, and 8% Contract. Highlights an 100% Remote job distribution.

Senior Machine Learning Scientist

Zanskar

Salt Lake City, UT • On-site, Remote

$88K - $121K/yr

Full-time

Posted 8 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.