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Remote Learning Sciences Jobs (NOW HIRING)

Webflow

Senior Staff Machine Learning Scientist, Assets

OR · On-site +1

$91K - $124K/yr

We're looking for a Senior Staff Machine Learning Scientist to help us solve challenging problems ... Remote-first (United States; BC & ON, Canada) * Full-time * Permanent * Exempt * Our cash ...

Webflow

Senior Staff Machine Learning Scientist, Assets

$93K - $127K/yr

We're looking for a Senior Staff Machine Learning Scientist to help us solve challenging problems ... Remote-first (United States; BC & ON, Canada) * Full-time * Permanent * Exempt * Our cash ...

Freenome

Senior Machine Learning Scientist

Brisbane, CA · On-site

$110K - $150K/yr

At Freenome, we are seeking a Senior Machine Learning Scientist to help grow the Machine Learning ... remote. What you'll do: * Independently pursue cutting edge research in AI applied to biological ...

Freenome

Staff Machine Learning Scientist

Brisbane, CA · On-site +1

$199K - $283K/yr

At Freenome, we are seeking a Staff Machine Learning Scientist to help grow the Machine Learning ... remote. What you'll do: * Independently pursue cutting edge research in AI applied to biological ...

Freenome

Senior Machine Learning Scientist

Brisbane, CA · On-site +1

$110K - $150K/yr

At Freenome, we are seeking a Senior Machine Learning Scientist to help grow the Machine Learning ... remote. What you'll do: * Independently pursue cutting edge research in AI applied to biological ...

Freenome

Staff Machine Learning Scientist

Brisbane, CA · On-site

$199K - $283K/yr

At Freenome, we are seeking a Staff Machine Learning Scientist to help grow the Machine Learning ... remote. What you'll do: * Independently pursue cutting edge research in AI applied to biological ...

StackAdapt

We are searching for a talented Senior/Staff Applied Machine Learning Scientist to join our ... StackAdapt is a remote-first company, and we are open to candidates located anywhere in the US or ...

Outsmart

Faculty Lead & Learning Engineer - Sciences

Lehi, UT · On-site

$96K - $126K/yr

About the role The Faculty Lead & Learning Engineer - Sciences is Outsmart's designated faculty ... Remote work days * Lunch provided in-office daily * Working with super talented people who want to ...

Natera

Machine Learning Scientist, Multimodal AI

$124K - $171K/yr

Natera is hiring a Machine Learning Scientist to join our AI and computational biology team. This ... Remote USA $124,800-$171,600 USD OUR OPPORTUNITY Natera™ is a global leader in cell-free DNA ...

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Showing results 1-20

All JobsRemote Learning Sciences Jobs

Remote Learning Sciences information

See salary details

$11K

$83.9K

$140K

How much do remote learning sciences jobs pay per year?

As of Jun 25, 2026, the average yearly pay for remote learning sciences in the United States is $83,885.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,000.00 and $139,000.00 per year, depending on experience, location, and employer.

What is the difference between Remote Learning Sciences vs Remote Instructional Designer?

AspectRemote Learning SciencesRemote Instructional Designer
Required CredentialsMaster's or PhD in Education, Learning Sciences, Psychology, or related fieldsBachelor's or Master's in Education, Instructional Design, or related areas
Work EnvironmentResearch-focused, data-driven, often involves analyzing learning behaviorsDesign-focused, creating online courses and materials for various clients or institutions
Employer & Industry UsageEducational institutions, research organizations, edtech companiesEducational institutions, corporate training, e-learning companies
Common Search & ComparisonYesNo

Remote Learning Sciences professionals focus on understanding how people learn through research and data analysis, often working in academic or research settings. In contrast, Remote Instructional Designers primarily create and develop online learning materials and courses. While both roles involve online education, Learning Sciences emphasizes research and theory, whereas Instructional Design centers on practical course development.

More about Remote Learning Sciences jobs
What cities are hiring for Remote Learning Sciences jobs? Cities with the most Remote Learning Sciences job openings:
What are the most commonly searched types of Learning Sciences jobs? The most popular types of Learning Sciences jobs are:
What states have the most Remote Learning Sciences jobs? States with the most job openings for Remote Learning Sciences jobs include:
What job categories do people searching Remote Learning Sciences jobs look for? The top searched job categories for Remote Learning Sciences jobs are:
Remote Learning Sciences jobs near you
Infographic showing various Remote Learning Sciences job openings in the United States as of June 2026, with employment types broken down into 33% Full Time, 33% Part Time, and 34% Contract. Highlights an 100% Remote job distribution, with an average salary of $83,885 per year, or $40.3 per hour.

Senior Machine Learning Scientist

Zanskar

Salt Lake City, UT • On-site, Remote

$88K - $121K/yr

Full-time

Posted 5 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.