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Remote Paper Machine Jobs (NOW HIRING)

Zanskar

Senior Machine Learning Scientist

Salt Lake City, UT · On-site +1

$88.50K - $121K/yr

Salt Lake City, UT, Hybrid (3 days in office, 2 days can be remote) Benefits Eligible: Yes Manager ... Reproduce & adapt: you can implement ideas from papers and new frameworks quickly, then harden the ...

SmarterDx

Staff Machine Learning Research Scientist

$220K - $260K/yr

This role is fully remote within the US** What You'll Do * Lead end-to-end ML research, from idea ... Contribute to external presence through papers, talks, and recruiting What You Bring * Strong track ...

Zanskar

Senior Machine Learning Scientist

Salt Lake City, UT · On-site +1

$88.50K - $121K/yr

Salt Lake City, UT, Hybrid (3 days in office, 2 days can be remote) Benefits Eligible: Yes Manager ... Reproduce & adapt: you can implement ideas from papers and new frameworks quickly, then harden the ...

Futran Tech Solutions Pvt. Ltd.

ML Engineer Lead

Edison, NJ · Remote

$103.90K - $136.80K/yr

Edison, NJ( Remote) : * Specialization below Machine Learning EngineeringComputer Vision and ... Implement papers on State Of The Art methodologies on video segmentation video classification ...

AlixaRx

Clinical Pharmacist

Rapid City, SD · Remote

$117K - $139.70K/yr

Manage installation of new remote dispensing machines at long term care facilities, including ... Replace refillable supplies on equipment and computers, including toner cartridges, paper stock ...

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Remote Paper Machine information

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How much do remote paper machine jobs pay per hour?

As of Jun 2, 2026, the average hourly pay for remote paper machine in the United States is $21.33, according to ZipRecruiter salary data. Most workers in this role earn between $18.75 and $22.84 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Paper Machine Operator, and why are they important?

To thrive as a Paper Machine Operator, you need strong mechanical aptitude, attention to detail, and a high school diploma or equivalent, with some roles requiring technical training. Familiarity with industrial control systems, quality monitoring tools, and safety protocols is often necessary. Problem-solving skills, teamwork, and clear communication help operators adapt to changing production needs and resolve issues quickly. These skills are crucial for maintaining efficient, safe, and high-quality paper production in a manufacturing environment.

What are some common challenges faced by remote paper machine operators, and how can they be addressed?

Remote paper machine operators often encounter challenges related to communication and troubleshooting equipment issues from a distance. Since they are not physically present on the production floor, they rely heavily on real-time data, remote monitoring tools, and close coordination with on-site staff. Building strong communication channels and staying updated with the latest monitoring technologies can help mitigate these challenges. Regular virtual meetings and clear documentation also ensure that remote operators are aligned with the rest of the team and can address issues promptly.

What are remote paper machine operators?

Remote paper machine operators are professionals who monitor and control the operations of paper manufacturing machinery from a remote location, often using advanced digital systems and monitoring tools. Their responsibilities include ensuring that the machines run efficiently, troubleshooting issues, and maintaining product quality without being physically present at the manufacturing site. This role leverages technology to enable real-time data analysis and machine adjustments, improving safety and operational efficiency. Remote paper machine operators typically collaborate with on-site staff and technical teams to resolve issues and optimize production.

What is the difference between Remote Paper Machine vs Paper Machine Operator?

AspectRemote Paper MachinePaper Machine Operator
CredentialsHigh school diploma, technical trainingHigh school diploma, technical training
Work EnvironmentRemote, often from home or officeOn-site at paper mill
Industry UsageInvolved in monitoring, data analysis, and remote control systemsDirect operation and maintenance of paper machines
Job FocusSupervision, troubleshooting remotely, system managementHands-on machine operation, adjustments, and troubleshooting

The main difference is that Remote Paper Machine roles focus on overseeing and managing paper production remotely, while Paper Machine Operators work directly on-site to operate and maintain the machinery. Both roles require technical skills, but their work environments and daily tasks differ significantly.

More about Remote Paper Machine jobs
What cities are hiring for Remote Paper Machine jobs? Cities with the most Remote Paper Machine job openings:
What are the most commonly searched types of Paper Machine jobs? The most popular types of Paper Machine jobs are:
What states have the most Remote Paper Machine jobs? States with the most job openings for Remote Paper Machine jobs include:
What job categories do people searching Remote Paper Machine jobs look for? The top searched job categories for Remote Paper Machine jobs are:
Remote Paper Machine jobs near you
Infographic showing various Remote Paper Machine job openings in the United States as of May 2026, with employment types broken down into 75% Full Time, 20% Part Time, and 5% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $44,363 per year, or $21.3 per hour.

Senior Machine Learning Scientist

Zanskar

Salt Lake City, UT • On-site, Remote

$88.50K - $121K/yr

Full-time

Posted 12 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.