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Machine Learning Scientist Jobs in Utah (NOW HIRING)

... building large-scale machine learning, predictive modeling, and advanced analytics tools ... Qualifications : Required : • Undergraduate degree in Data Science, Statistics, Mathematics ...

Senior Data Scientist

Lehi, UT · On-site

$107K - $183K/yr

As a Senior Data Scientist, you will collaborate with cross-functional stakeholders to identify ... Proficient creating machine learning, predictive modeling, and advanced analytics tools tailored to ...

As a Senior Data Scientist, you will collaborate with cross-functional stakeholders to identify ... Proficient creating machine learning, predictive modeling, and advanced analytics tools tailored to ...

Senior Machine Learning Engineer

Sandy, UT · On-site

$113K - $150K/yr

As Senior Machine Learning Engineer, you will own the evaluation and optimization of speech ... MS in computer science, electrical engineering, computational linguistics, or a related field with ...

Role - Lead, mentor and grow the data science team and tech stack focused on developing production-grade services and capabilities - Plan and direct data science / machine learning projects within ...

Job Brief Data Science, Machine Learning, Programming Are you VIGILANT about your career? RealmOne definitely is! RealmOne was built on the principle that people matter first and foremost. We believe ...

Lead Data Scientist

Draper, UT · On-site +1

$138K - $272K/yr

Advanced machine learning modeling and/or technical expertise in developing market differentiation data science products. * Experience in bank card/credit card business, consulting, retail, marketing ...

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Machine Learning Scientist information

What is a Machine Learning Scientist job?

A Machine Learning Scientist researches, develops, and applies machine learning models to solve complex problems. They work on designing algorithms, improving model performance, and analyzing large datasets to extract valuable insights. Their role often involves experimenting with new techniques, optimizing existing models, and collaborating with engineers and data scientists to deploy solutions. Machine Learning Scientists typically have expertise in statistics, mathematics, and programming languages like Python. They work in industries such as healthcare, finance, and technology to drive innovation using artificial intelligence.

What are the typical daily tasks and collaboration opportunities for a Machine Learning Scientist?

A typical day for a Machine Learning Scientist involves collecting and analyzing large datasets, designing and training machine learning models, and evaluating model performance to ensure accuracy and reliability. You'll often collaborate with data engineers, software developers, and domain experts to define project goals, prepare data, and integrate solutions into production systems. Regular team meetings, code reviews, and brainstorming sessions are common, fostering an environment of shared learning and problem-solving. This collaborative structure not only enhances project outcomes but also offers valuable opportunities for continuous professional growth and skill development.

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

To thrive as a Machine Learning Scientist, you need strong skills in mathematics, statistics, programming (typically in Python or R), and a graduate degree in computer science, data science, or a related field. Expertise in machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), proficiency with data processing tools, and experience with cloud platforms (like AWS or GCP) are commonly required; certifications in these can be advantageous. Critical thinking, problem-solving, and effective communication are important soft skills for collaborating with cross-functional teams and conveying complex concepts. These abilities enable Machine Learning Scientists to build effective models, deliver actionable insights, and drive innovation within organizations.

What are the most commonly searched types of Machine Learning Scientist jobs in Utah? The most popular types of Machine Learning Scientist jobs in Utah are:
Infographic showing various Machine Learning Scientist job openings in Utah as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.
Machine Learning Platform Engineer - Backend Services (Utah)

Machine Learning Platform Engineer - Backend Services (Utah)

Waystar

Lehi, UT • On-site

Full-time

Posted 20 days ago


Job description

Job Summary:
Waystar is a leading company in healthcare payment solutions, seeking a Machine Learning Platform Engineer - Backend Services to enhance their platform for predictive models and data analysis. The role involves developing and maintaining machine learning frameworks, collaborating with data science teams, and ensuring the reliability of production systems.
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
Qualifications:
Required:
• 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:
• Familiarity with ClearML, Triton, PyTorch, and TensorFlow
• Familiarity with statistics and healthcare domain
• Proven expertise in successful large project/build management and execution
Company:
Waystar is a technology platform that provides healthcare revenue cycle management solutions. Founded in 2017, the company is headquartered in Louisville, USA, with a team of 1001-5000 employees. The company is currently Late Stage.