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Hourly Remote Machine Learning Engineer Jobs in Kaysville, UT

Suralink Inc

Sr. Software Engineer

Salt Lake City, UT · Remote

$125K - $165K/yr

Experience with machine learning or generative AI prompt engineering * Caching/NoSQL datastores ... Remote-friendly policy * Medical/vision/dental insurance * Life, short-term disability, and ...

Enova International

Be Seen First

Call Center Sales Representative (Remote)

Salt Lake City, UT · Remote

$17/hr

This role is entirely remote; however, candidates must reside within 100 miles of either Chicago ... our AI and machine learning-powered ColossusTM platform. We serve non-prime consumers and ...

TSMG

AI/ML Data Contributor

Salt Lake City, UT · Remote

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

TSMG

AI/ML Data Contributor

Salt Lake City, UT · Remote

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

Healthcare

Data science software developer

Murray, UT · On-site +1

$124K - $170K/yr

... another machine learning framework * 3 years of experience developing cloud-hosted applications ... Remote Relocation Assistance: Not authorized Must be legally authorized to work in country of ...

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Hourly Remote Machine Learning Engineer information

See Kaysville, UT salary details

$23.2K

$38.7K

$80.1K

How much do hourly remote machine learning engineer jobs pay per year?

As of Aug 25, 2026, the average yearly pay for hourly remote machine learning engineer in Kaysville, UT is $38,737.00, according to ZipRecruiter salary data. Most workers in this role earn between $29,600.00 and $41,800.00 per year, depending on experience, location, and employer.

What does an hourly remote machine learning engineer do?

An Hourly Remote Machine Learning Engineer is a professional who develops and implements machine learning models and algorithms for clients or employers on an hourly contract basis, all while working from a remote location. Their responsibilities typically include data preprocessing, model selection, training, testing, and deployment. They collaborate with teams via online tools, manage their own schedules, and deliver results according to project requirements. This role allows for flexibility and the opportunity to work on diverse projects across different industries.

What are some common challenges faced by hourly remote machine learning engineers, and how can they be addressed?

Hourly remote machine learning engineers often encounter challenges such as managing time effectively across multiple projects, ensuring clear communication with distributed teams, and accessing necessary data or computing resources remotely. Building strong routines for regular check-ins and using collaborative tools can help maintain alignment with project goals. Additionally, proactively clarifying expectations and deliverables with clients or team leads can minimize misunderstandings and improve productivity in a remote, hourly environment.

What are the key skills and qualifications needed to thrive as an hourly remote machine learning engineer, and why are they important?

To thrive as an Hourly Remote Machine Learning Engineer, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and experience with data preprocessing, typically supported by a relevant degree or equivalent experience. Familiarity with tools and frameworks such as TensorFlow, PyTorch, scikit-learn, cloud platforms (e.g., AWS, GCP), and version control systems like Git is essential. Excellent time management, self-motivation, and clear communication skills help you collaborate effectively across distributed teams and manage project-based work. These skills and qualities are vital for delivering high-quality results independently, meeting deadlines, and adapting to the dynamic needs of remote projects.

What job categories do people searching Hourly Remote Machine Learning Engineer jobs in Kaysville, UT look for?

The top searched job categories for Hourly Remote Machine Learning Engineer jobs in Kaysville, UT are:

What cities near Kaysville, UT are hiring for Hourly Remote Machine Learning Engineer jobs?

Cities near Kaysville, UT with the most Hourly Remote Machine Learning Engineer job openings:

Hourly Remote Machine Learning Engineer jobs near you
Infographic showing various Hourly Remote Machine Learning Engineer job openings in Kaysville, UT as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 25% Part Time, and 1% Contract. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution, with an average salary of $38,737 per year, or $18.6 per hour.

Internship - Machine Learning Engineer

Smule

Salt Lake City, UT • Remote

Other

Re-posted 23 days ago

Job description

Smule has been on a mission to bring the world together through music since 2008. Music is much more than listening… it's about creating, sharing, discovering, participating, and connecting with people. With dozens of millions of monthly active users creating over 20 million songs every day, Smule is connecting people all over the world through the joy of making music and transforming the music landscape from one of passive listening to collaborative creative expression and active engagement.


About the Role:

We are looking for a Machine Learning Engineer to own the end-to-end lifecycle of ML models in production at Smule, from training and optimization through deployment, monitoring, and iteration. You will work closely with research scientists to bring models off the bench and into scalable, reliable systems that serve millions of users. The ideal candidate is a strong engineer first, with deep practical knowledge of ML systems, a passion for reliability, and an eye for performance.


We strongly encourage candidates with non-traditional backgrounds to apply. If your path into ML engineering came through backend systems, DevOps, audio software, data engineering, or another field, we want to hear from you.


What You'll Be Doing:

  • Design, build, and maintain production ML pipelines encompassing data ingestion, feature engineering, model training, evaluation, and deployment.
  • Optimize models for production constraints including latency, throughput, memory footprint, and cost, using techniques such as quantization, distillation, pruning, and efficient serving architectures.
  • Implement robust monitoring, alerting, and observability for deployed models, covering data drift, prediction quality, and system health.
  • Collaborate with research scientists to integrate new model architectures and training techniques into production systems with minimal friction.
  • Build and improve CI/CD pipelines for ML, including automated testing, validation gates, and staged rollouts.
  • Manage compute infrastructure and costs, making informed tradeoffs between performance, reliability, and budget.


What We're Looking For:

  • Degree (B.S., M.S., or Ph.D.) in Computer Science, Software Engineering, Electrical Engineering, or a related technical discipline, or currently pursuing one.
  • Strong proficiency in Python and experience with deep learning serving (TorchServe, Triton, vLLM, or equivalent).
  • Solid understanding of systems engineering: networking, storage, containerization, orchestration, and monitoring.
  • Ability to reason about tradeoffs between latency, throughput, cost, and model quality.


Bonus Points For:

  • Experience serving large language models or other generative models at scale.
  • Familiarity with audio/music processing pipelines and real-time inference constraints.
  • Experience with Bayesian optimization, bandit algorithms, or adaptive experimentation platforms.
  • Contributions to open-source ML infrastructure projects.


Smule is an Equal Opportunity Employer and considers all qualified applicants without regard to race, color, religion, sex, gender identity or expression, sexual orientation, national origin, ancestry, age, disability, medical condition, genetic information, marital status, military or veteran status, or any other protected characteristic under federal, state, or local law.


We are committed to creating an inclusive environment for all employees and applicants. If you require a reasonable accommodation during the application or interview process, please let us know.