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Remote Machine Learning Engineer Jobs in Clearfield, UT

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Remote Machine Learning Engineer information

See Clearfield, UT salary details

$29.4K

$120K

$180.4K

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

As of Jul 9, 2026, the average yearly pay for remote machine learning engineer in Clearfield, UT is $120,030.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,600.00 and $144,500.00 per year, depending on experience, location, and employer.

What engineers make $300,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually. High compensation often reflects expertise, leadership roles, or working in competitive industries such as tech or finance, especially in organizations valuing AI development.

What are some typical challenges faced by Remote Machine Learning Engineers, and how are they addressed?

Remote Machine Learning Engineers often face challenges such as coordinating across different time zones, ensuring smooth communication with team members, and accessing large datasets or secure environments remotely. Organizations commonly address these by using robust collaboration tools (like Slack, GitHub, and Jira), establishing clear documentation, and setting regular virtual meetings to maintain alignment. Many companies also provide secure remote environments or VPN access for handling sensitive data and code. Proactive communication and organized workflows help mitigate these challenges, enabling engineers to remain productive and connected to their teams.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $500,000 or more annually, especially in high-cost-of-living areas or within top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role is unlikely to be fully replaced by AI itself. Instead, AI tools can augment their work by automating routine tasks, allowing MLEs to focus on complex problem-solving, model optimization, and system integration. Continuous learning and expertise in programming, data handling, and model evaluation remain essential for MLEs in an evolving AI landscape.

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

To thrive as a Remote Machine Learning Engineer, you need a strong background in computer science, mathematics, and experience with machine learning algorithms, typically supported by a relevant degree and prior project work. Proficiency with programming languages like Python, machine learning frameworks such as TensorFlow or PyTorch, and familiarity with cloud computing platforms is crucial, and certifications like AWS Certified Machine Learning can enhance your profile. Excellent communication, self-motivation, and time-management skills are also essential for collaborating across remote teams and meeting project goals. These combined technical and soft skills are vital for developing effective machine learning solutions while ensuring productivity and collaboration in a virtual work environment.

What is a Remote Machine Learning Engineer job?

A Remote Machine Learning Engineer designs, develops, and deploys machine learning models while working from a remote location. They preprocess data, train and optimize models, and integrate them into production systems. Their role often involves collaborating with data scientists, software engineers, and stakeholders to solve complex problems using AI. Strong programming skills in Python, experience with ML frameworks like TensorFlow or PyTorch, and cloud computing knowledge are essential. Remote ML engineers must also communicate effectively and manage their time efficiently to work asynchronously with teams.

Can ML engineers work remotely?

Yes, many machine learning engineers work remotely, especially in roles that involve programming, data analysis, and model development using tools like Python, TensorFlow, or PyTorch. Remote work arrangements depend on the employer's policies and the specific project requirements, but it is common in the tech industry for ML engineers to work from home or other locations.
What job categories do people searching Remote Machine Learning Engineer jobs in Clearfield, UT look for? The top searched job categories for Remote Machine Learning Engineer jobs in Clearfield, UT are:
What cities near Clearfield, UT are hiring for Remote Machine Learning Engineer jobs? Cities near Clearfield, UT with the most Remote Machine Learning Engineer job openings:
Internship - Machine Learning Engineer

Internship - Machine Learning Engineer

Smule

Salt Lake City, UT • Remote

Other

Re-posted 6 days ago


Job description

Salary:

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.