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Remote Machine Learning Jobs in Utah (NOW HIRING)

Wsgr

Innovations and AI Solutions Engineer

Salt Lake City, UT · On-site +1

$116.88K - $158.13K/yr

This position is available as a hybrid or remote work schedule. Essential Duties, Responsibilities ... Design, build and implement machine learning models, including the development of AI Models and ...

Tendo

Principal Data Scientist

Salt Lake City, UT · On-site +1

$131.75K - $178.25K/yr

We're looking for someone who brings an AI-native mindset, has hands-on experience applying AI or machine learning to real-world problems, and is passionate about exploring how emerging AI ...

DataAnnotation

Staff Software Engineer

Salt Lake City, UT · On-site +1

$60/hr

... remote work and setting your own schedule. We are looking for proficient programmers to help ... machine learning, and other engineers -- who are driving real‐world impact in AI development. Our ...

Cicero Group

Senior AI Developer

Salt Lake City, UT · On-site +1

$52.75 - $69.75/hr

... or machine learning applications * Hands-on experience building with LLMs, including RAG ... Remote employees will be expected to travel to an office periodically.

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Remote Machine Learning information

See Utah salary details

$23.2K

$38.8K

$80.1K

How much do remote machine learning jobs pay per year?

As of May 29, 2026, the average yearly pay for remote machine learning in Utah is $38,767.00, according to ZipRecruiter salary data. Most workers in this role earn between $29,600.00 and $41,900.00 per year, depending on experience, location, and employer.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Engineer, and why are they important?

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

What are some effective strategies for collaborating with team members while working remotely as a Machine Learning Engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

Is ML full of coding?

Machine Learning (ML) roles often involve significant coding, especially in programming languages like Python or R, to develop algorithms and models. However, some positions focus more on data analysis, feature engineering, or model evaluation, which may require less coding but still involve technical skills and understanding of ML concepts.

What is the difference between Remote Machine Learning vs Data Scientist?

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

More about Remote Machine Learning jobs
What are the most commonly searched types of Machine Learning jobs in Utah? The most popular types of Machine Learning jobs in Utah are:
What job categories do people searching Remote Machine Learning jobs in Utah look for? The top searched job categories for Remote Machine Learning jobs in Utah are:
What cities in Utah are hiring for Remote Machine Learning jobs? Cities in Utah with the most Remote Machine Learning job openings:
Remote Machine Learning jobs near you
Principal Applied Scientist

Principal Applied Scientist

Relativity

Salt Lake City, UT • On-site, Remote

Other

Medical, Retirement

Posted 17 days ago

Job description

Posting Type

Remote/Hybrid

Job Overview

WHO WE ARE
Relativity is a leading legal data intelligence company building technology that helps users organize data, discover the truth, and act on it with confidence. Our AI-powered, cloud platform, RelativityOne, transforms massive volumes of complex information into actionable insights for litigation, investigations, regulatory inquiries, data breach responses, and other highstakes legal work where accuracy, trust, and defensibility are essential.
Relativity aiR is redefining document review through agentic AI systems that reason, cite their decisions, and scale across millions of documents. These systems automate complex legal workflows while keeping humans in the loop, enabling legal professionals to focus on what matters most.
WHAT WE DO
At Relativity, we are building a worldclass Applied Science organization focused on pushing the boundaries of intelligent systems in one of the most demanding and consequential domains: the legal system.
Applied Science Team
The Applied Science team sits at the core of Relativity's AI development. We are responsible for designing, validating, and operating the intelligent systems behind Relativity aiR. Our work goes far beyond simple model integrations. We build agentic systems that reason over documents, validate decisions statistically, remain auditable and defensible, and operate reliably at massive scale. Trust, reliability, and responsibility are foundational to everything we build.
Our team values curiosity, experimentation, rigor, and collaboration. We move quickly, validate assumptions with evidence, and simplify aggressively to deliver systems that are safe, reliable, and impactful in production.

Job Description and Requirements

ABOUT THE ROLE

As a Principal Applied Scientist, Reliability, you will lead the design and validation of intelligent systems that customers can trust in highstakes legal workflows. You will operate endtoend: understanding the problem space, designing solutions, validating them statistically, and bringing them to production in partnership with engineering, product, and customerfacing teams.

This role is ideal for an experienced applied scientist who thrives at the intersection of modeling, experimentation, and realworld system reliability, and who is motivated by building AI systems that are not only powerful, but also defensible, interpretable, and safe by design.

WHAT YOU'LL DO

  • Write productionquality code that solves real customer problems and scales cleanly, with systems designed to be easy to ship, operate, and maintain
  • Collaborate closely with fellow Applied Scientists as well as Engineers, Product Managers, Designers, and Customers
  • Design and execute statistically sound experiments and automate them into reusable benchmarks and evaluation frameworks
  • Rapidly prototype AI and MLpowered solutions and mature them into reliable, scalable production models
  • Select the appropriate modeling approach for each problem, ranging from classical machine learning techniques to frontier large language models
  • Validate model behavior rigorously using evidence, metrics, and experimentation, remaining open to changing course when the data demands it
  • Contribute to building intelligent systems that reason, cite their decisions, and operate defensibly at scale
  • Help push the boundaries of agentic AI while ensuring systems remain auditable, reliable, and responsible

WHAT WE'RE LOOKING FOR

  • 8+ years of professional experience in applied science, machine learning, or a closely related field
  • Master's or Ph.D. in Computer Science, Statistics, Applied Mathematics, or a related quantitative discipline, or equivalent professional experience
  • Proven ability to move quickly from prototype to production, simplifying complex ideas into robust systems
  • Experience reading, validating, and applying research with a healthy level of skepticism
  • Experience across a wide range of modeling techniques, from classical machine learning to largescale generative models
  • Familiarity with modern MLOps tooling and practices, including containers, workflow orchestration, deployment patterns, telemetry, and experimentation systems
  • Strong Python programming skills and experience with common data and ML libraries such as numpy, PyTorch, scikitlearn, and PySpark
  • Strong communication skills, with the ability to explain complex technical concepts clearly to both technical and nontechnical audiences
  • Endtoend ownership mindset, with the ability to understand new problem spaces, design solutions, and bring them to market alongside engineering, product, and support partners
  • A collaborative, curious, and adaptable approach, with comfort leading, questioning assumptions, and learning from failure

WHY WE COULD BE A GREAT FIT

HighImpact Problems

  • Work on intelligent systems that operate in one of the most highstakes domains, where trust, reliability, and defensibility truly matter.

Agentic AI at Scale

  • Build and extend AI systems that reason across millions of documents, cite their decisions, and automate complex legal workflows.

Scientific Rigor and RealWorld Impact

  • Apply deep experimentation and statistical validation to systems that ship to real customers and influence real outcomes.

Leadership and Growth

  • Lead technically while continuously learning in a thoughtful, supportive, and intellectually rich Applied Science organization.

Collaborative Culture

  • Join a team that values kindness, curiosity, technical excellence, and shared ownership of outcomes.

Compensation and Benefits

  • Competitive compensation, health and retirement programs, discretionary time off (DTO), parental leave for primary and secondary caregivers, companywide breaks, wellness resources, and an equity program.

Relativity is committed to competitive, fair, and equitable compensation practices.

This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives.

The expected salary range for this role is between following values:

$224,000 and $336,000

The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position.

Required Skills:

Algorithms, Data Analysis, Machine Learning (ML), Natural Language, Python (Programming Language), Reinforcement Learning, Researching, Scientific Writing, Statistical Models, Technical Leadership

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