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Machine Learning Engineer Jobs in Provo, UT (NOW HIRING)

Entrata

Senior Machine Learning Engineer

Lehi, UT · On-site +1

$144K - $233K/yr

We are seeking a Senior Machine Learning Engineer to help build and scale Entrata's applied AI capabilities. This role will focus on adapting and fine-tuning foundation models for property management ...

Entrata

Senior Machine Learning Engineer

Lehi, UT · On-site +1

$144K - $233K/yr

We are seeking a Senior Machine Learning Engineer to help build and scale Entrata's applied AI capabilities. This role will focus on adapting and fine-tuning foundation models for property management ...

NICE

Senior Machine Learning Engineer

Sandy, UT · Hybrid

$99K - $136K/yr

As Senior Machine Learning Engineer, you will own the evaluation and optimization of speech-oriented AI models - covering real-time transcription and speech-to-speech systems across dozens of ...

NICE

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-oriented AI models - covering real-time transcription and speech-to-speech systems across dozens of ...

Entrata

Senior Machine Learning Engineer

Lehi, UT · On-site

$144K - $233K/yr

We're looking for a Senior AI and Machine Learning Engineer to help design, build, and optimize our AI and ML delivery platform. This role sits at the center of our AI strategy and focuses on ...

Berkadia

Senior Engineer - Machine Learning

Midvale, UT · Hybrid

$98K - $135K/yr

As a Senior Engineer, Machine Learning at Berkadia, you'll be at the forefront of applying cutting-edge machine learning and generative AI to redefine how the commercial real estate industry operates.

Socket.dev

Senior Engineer - Machine Learning

Midvale, UT · On-site

$140 - $210/hr

As a Senior Engineer, Machine Learning at Berkadia, you'll be at the forefront of applying cutting-edge machine learning and generative AI to redefine how the commercial real estate industry operates.

Berkadia

Senior Engineer - Machine Learning

Midvale, UT · On-site

$98K - $135K/yr

As a Senior Engineer, Machine Learning at Berkadia, you'll be at the forefront of applying cutting-edge machine learning and generative AI to redefine how the commercial real estate industry operates.

Varsity Tutors

Machine Learning Tutor

Provo, UT · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Spanish Fork, UT · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Patientco

Senior ML Engineer

Lehi, UT

$98K - $134K/yr

ABOUT THIS POSITION Summary We are seeking a highly skilled and innovative Machine Learning Engineer with a passion for building robust, efficient, and domain-specific AI systems using Language ...

Crew Career Center

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

ABOUT THIS POSITION Summary We are seeking a highly skilled and innovative Machine Learning Engineer with a passion for building robust, efficient, and domain-specific AI systems using Language ...

Waystar

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

ABOUT THIS POSITION Summary We are seeking a highly skilled and innovative Machine Learning Engineer with a passion for building robust, efficient, and domain-specific AI systems using Language ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Provo, UT

Machine Learning Engineer information

See Provo, UT salary details

$29.8K

$121.8K

$183K

How much do machine learning engineer jobs pay per year?

As of Aug 25, 2026, the average yearly pay for machine learning engineer in Provo, UT is $121,811.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,000.00 and $146,600.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs

What are the most commonly searched types of Machine Learning Engineer jobs in Provo, UT?

The most popular types of Machine Learning Engineer jobs in Provo, UT are:

What are popular job titles related to Machine Learning Engineer jobs in Provo, UT?

For Machine Learning Engineer jobs in Provo, UT, the most frequently searched job titles are:

What cities near Provo, UT are hiring for Machine Learning Engineer jobs?

Cities near Provo, UT with the most Machine Learning Engineer job openings:

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Provo, UT as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $121,811 per year, or $58.6 per hour.

Senior Machine Learning Engineer

Entrata

Lehi, UT • On-site, Remote

$144K - $233K/yr

Full-time

Re-posted 12 days ago

Entrata rating

7.9

Company rating: 7.9 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

131st of 246 rated software companies

Job description

Since 2003, Entrata has evolved from a visionary, student-led startup into a global leader in AI-driven property management technology. Today, we power the industry's most essential operating system, serving owners and residents worldwide through a comprehensive suite of intelligent leasing, payment, and communication tools powered by cutting-edge AI. With a proven track record of sustained growth and a global team of more than 2,200 employees, we offer the rare combination of established stability and high-velocity innovation. Recognized by the Silicon Slopes Hall of Fame and the Utah Business Fast 50, Entrata fosters a culture of radical transparency and entrepreneurial energy. At Entrata, we create an environment where different perspectives are valued and respected. Those perspectives challenge assumptions, strengthen our decisions, and raise the bar as we reshape the global living experience through AI-powered solutions.

We are seeking a Senior Machine Learning Engineer to help build and scale Entrata’s applied AI capabilities. This role will focus on adapting and fine-tuning foundation models for property management use cases, building reliable model training and evaluation pipelines, and deploying AI systems into production.

Responsibilities
  • Fine-tune and adapt large language models for Entrata-specific use cases using supervised fine-tuning and other post-training techniques.
  • Build scalable data preparation, curation, filtering, and synthetic data pipelines to support model training and evaluation.
  • Develop agentic AI systems that can reason across multi-step workflows, use tools, retrieve context, and operate reliably in production.
  • Build evaluation frameworks and benchmarks to measure model quality, safety, reliability, and task performance.
  • Optimize model inference, serving, and deployment for performance, cost, and scalability.
  • Partner with engineering, product, and data teams to integrate AI capabilities into Entrata products and workflows.
  • Help establish best practices for model experimentation, fine-tuning, evaluation, and deployment.
Minimum Qualifications
  • 5+ years of software engineering or machine learning engineering experience.
  • Hands-on experience fine-tuning, adapting, or deploying large language models.
  • Strong proficiency with Python and PyTorch or similar deep learning frameworks.
  • Experience building ML data pipelines, training workflows, and evaluation systems.
  • Experience deploying machine learning models into production environments.
  • Familiarity with modern LLM tooling, model serving, and inference frameworks.
  • Strong understanding of machine learning fundamentals and model performance tradeoffs.
Preferred Qualifications
  • Experience with supervised fine-tuning, preference optimization, or related post-training techniques.
  • Experience building agentic systems, tool-using models, or retrieval-based AI applications.
  • Experience with distributed training or GPU-based model workloads.
  • Familiarity with frameworks such as vLLM, DeepSpeed, FSDP, or similar technologies.
  • Experience working with enterprise or domain-specific AI applications.
  • Bachelor’s or advanced degree in Computer Science, Machine Learning, Engineering, or a related field, or equivalent practical experience.
This band covers the full salary range for the role. Your offer within this range will depend on factors like experience, skills, and internal equity.
 
Level - P4
Benefits:
Flexible and transparent culture with remote and hybrid work options, generous vacation time, and frequent company recharge days for work-life balance.

Comprehensive medical, dental, and vision coverage, including fertility benefits, available for eligible employees and their families.

HSA/FSA options and employer-paid disability benefits provided for eligible employees.

Access to 401(k) or similar retirement plans with employer matching for eligible employees, ensuring long-term financial security.

Wellness initiatives promoting physical and mental well-being, access to an onsite gym at HQ, gym memberships, mental health resources, wellness challenges, and employee assistance programs.

Entrata Cares programs offers opportunities for volunteerism, charity events, and giving back to our community.

Exclusive Previ cell phone plan and discounts on services or local business partnerships for additional employee benefits.

Bi-annual swag drops for employees

Currently, Entrata hires in Arizona, Idaho, Utah, Wyoming, Texas, North Carolina, Florida, Georgia, South Carolina, Ohio, Pennsylvania, and Illinois for Exempt roles and Arizona, Idaho, Utah, Wyoming, Texas, North Carolina, and Florida for Non-Exempt roles. 

Entrata is dedicated to creating a workplace where a diverse and inclusive team thrives in an environment free from discrimination. We provide equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, protected veteran status, or any other applicable characteristics protected by law.

It’s a great place to work! Will you join us?

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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