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Junior Machine Learning Jobs in Utah (NOW HIRING)

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... junior staff while upholding remarkable standards of quality and innovation in deliverables.

Senior Software Engineer

Lehi, UT · Hybrid

$115K - $151K/yr

Utilizing more than 66 trillion data points, sophisticated machine learning and AI models, Pattern ... Mentor junior engineers and contribute to a culture of continuous improvement and innovation. What ...

Senior Software Engineer

Lehi, UT · Hybrid

$115K - $151K/yr

Utilizing more than 66 trillion data points, sophisticated machine learning and AI models, Pattern ... Mentor junior engineers and contribute to a culture of continuous improvement and innovation. What ...

Senior Software Engineer

Lehi, UT · On-site

$115K - $151K/yr

Utilizing more than 66 trillion data points, sophisticated machine learning and AI models, Pattern ... Mentor junior engineers and contribute to a culture of continuous improvement and innovation. What ...

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 ... You are setting technical standards for the team, accelerating junior developers, and driving ...

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Junior Machine Learning information

See Utah salary details

$7

$24

$43

How much do junior machine learning jobs pay per hour?

As of Jul 9, 2026, the average hourly pay for junior machine learning in Utah is $24.54, according to ZipRecruiter salary data. Most workers in this role earn between $14.90 and $30.19 per hour, depending on experience, location, and employer.

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

AspectJunior Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML toolsBachelor's or Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentEntry-level projects, supervised tasks, team collaborationAdvanced analysis, model development, cross-functional teams
Industry UsageCommon in tech companies, startups, research labsWidespread across industries like finance, healthcare, tech

Junior Machine Learning roles focus on foundational ML tasks and learning on the job, while Data Scientists handle complex data analysis, model building, and strategic insights. The roles differ mainly in experience level and scope of responsibilities, but both require strong technical skills and familiarity with data tools.

What does a Junior Machine Learning Engineer do?

A Junior Machine Learning Engineer assists in the development and implementation of machine learning models and algorithms under the supervision of more experienced engineers. They typically help with data collection, cleaning, feature engineering, model training, and evaluation. Junior engineers may also write code, test prototypes, and contribute to improving model performance while learning best practices in the field. Their role often involves collaborating with data scientists and software engineers to integrate machine learning solutions into products or services.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in programming, data analysis, and deep learning. These roles usually involve leadership, strategic planning, and expertise with tools like TensorFlow or PyTorch, and may require multiple years of experience and relevant certifications.

What types of projects and tasks can a Junior Machine Learning professional typically expect to work on in their first year?

As a Junior Machine Learning professional, you’ll often support senior data scientists and engineers by preparing data, implementing basic algorithms, and assisting with model evaluation. Your daily tasks may include data cleaning, feature engineering, running experiments, and writing code to automate data pipelines. You might also help document processes and present your findings to team members. While the work is often collaborative, you’ll have opportunities to take ownership of smaller projects and progressively contribute to larger initiatives as you gain experience.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within top tech companies. Compensation often includes base salary, bonuses, and stock options. Achieving this level typically requires years of specialized experience and a strong track record of impactful projects.

Can I get an AI job with no experience?

Entry-level machine learning roles, such as Junior Machine Learning positions, often require some foundational knowledge of programming, mathematics, and data analysis. While prior experience is beneficial, candidates can improve their chances by completing relevant online courses, building projects, and gaining familiarity with tools like Python and TensorFlow.

Which 3 jobs will survive AI?

Junior Machine Learning roles are likely to persist as they require specialized knowledge, critical thinking, and domain expertise that AI cannot fully replicate. Jobs involving complex problem-solving, creativity, and human interaction, such as data scientists, AI ethics specialists, and machine learning engineers, are also expected to remain in demand. Continuous learning and adapting to new tools will be essential for these roles to stay relevant.

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

To thrive as a Junior Machine Learning Engineer, you need a solid understanding of programming (especially Python), basic statistics, linear algebra, and familiarity with machine learning concepts, typically supported by a relevant degree or coursework. Proficiency in tools and frameworks like scikit-learn, TensorFlow, PyTorch, and version control systems such as Git is often expected. Strong problem-solving abilities, curiosity, and effective communication are crucial soft skills for collaborating with teams and explaining technical concepts. These skills and qualities are important because they enable you to contribute effectively to building, testing, and improving machine learning models in real-world applications.
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 are popular job titles related to Junior Machine Learning jobs in Utah? For Junior Machine Learning jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Junior Machine Learning jobs? Cities in Utah with the most Junior Machine Learning job openings:
Platform Engineer Machine Learning (Utah)

Platform Engineer Machine Learning (Utah)

Waystar

Lehi, UT • On-site

Full-time

Medical, Retirement, PTO

Re-posted 11 days ago


Job description

ABOUT THIS POSITION
We are looking for a Machine Learning Platform Engineer - Backend Services that will help us build out the platform that supports the training and application of our predictive models and performs deep analysis to extract machine consumable meaning from unstructured clinical documentation. You will be joining a small team that has become one of the top players in our field in just two years. Because we work on the cutting edge of a lot of technologies, we need someone who is a creative problem solver, resourceful in getting things done, and productive working independently or collaboratively. You will be accessing our enormous amount of data to help drive our future innovation.
WHAT YOU'LL DO
Responsibilities:
  • Develop and enhance the machine learning platform to manage the full model life cycle

  • Build frameworks and tools to enable the data science team developing and enhancing predictive models, support scalable real-time predictions in production

  • Design and implement data engineering solutions for model training

  • Expand NLP capabilities with advanced analysis techniques to improve text understanding

  • Design and implement high-performance, scalable services and applications

  • Collaborate with team members to create integrated solutions and ensure timely delivery of quality software and documentation

  • Understand and adhere to development standards for consistency across teams

  • Perform in-depth technical and performance analyses to troubleshoot production issues

  • Monitor and maintain production systems for reliability and efficiency

WHAT YOU'LL NEED
  • Minimum Requirements (Education, certifications and experience):
  • Bachelor's degree in Computer Science or related area, Masters preferred

  • 7+ years of professional experience writing Python or Java code, with at least 3 years building data platforms

  • Expert proficiency with SQL
  • NLP

  • Seasoned practitioner of engineering best practices such as CI/CD and automated testing

  • Comfort working in a Linux environment

  • Passion for exploring, applying and following the evolution of cutting edge technologies related to AI, machine learning, NLP and large scale data processing

  • Professional experience with MLOps, Docker, Kubernetes, relational databases (PostgreSQL preferred), Kafka, REST API design, and microservices application architectures

  • Experience with public cloud solutions, such as AWS or GCP

  • Proven track record of successful delivery of progressively complex technical projects

  • Coaching and mentoring junior engineers in the team

  • Team player DNA with a positive, self-starter attitude

  • Attention to detail, highly organized, with an absolute focus on quality of work

Preferred Requirements:
  • Familiarity with ClearML, Triton, PyTorch, and TensorFlow

  • Familiarity with statistics and healthcare domain

  • Proven expertise in successful large project/build management and execution

ABOUT WAYSTAR
Through a smart platform and better experience, Waystar helps providers simplify healthcare payments and yield powerful results throughout the complete revenue cycle.
Waystar's healthcare payments platform combines innovative, cloud-based technology, robust data, and unparalleled client support to streamline workflows and improve financials so providers can focus on what matters most: their patients and communities. Waystar is trusted by 1M+ providers, 1K+ hospitals and health systems, and is connected to over 5K commercial and Medicaid/Medicare payers. We are deeply committed to living out our organizational values: honesty; kindness; passion; curiosity; fanatical focus; best work, always; making it happen; and joyful, optimistic & fun.
Waystar products have won multiple Best in KLAS® or Category Leader awards since 2010 and earned multiple #1 rankings from Black Book™ surveys since 2012. The Waystar platform supports more than 500,000 providers, 1,000 health systems and hospitals, and 5,000 payers and health plans. For more information, visit waystar.com or follow @Waystar on Twitter.
WAYSTAR PERKS
  • Competitive total rewards (base salary + bonus, if applicable)
  • Customizable benefits package (3 medical plans with Health Saving Account company match)
  • We offer generous paid time off for our non-exempt team members, starting with 3 weeks + 13 paid holidays, including 2 personal floating holidays. We also offer flexible time off for our exempt team members + 13 paid holidays
  • Paid parental leave (including maternity + paternity leave)
  • Education assistance opportunities and free LinkedIn Learning access
  • Free mental health and family planning programs, including adoption assistance and fertility support
  • 401(K) program with company match
  • Pet insurance
  • Employee resource groups

Waystar is proud to be an equal opportunity workplace. We celebrate, value, and support diversity and inclusion. Qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, marital status, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.
This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.