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Remote Machine Learning Engineer Jobs in Salt Lake City, UT

Entrata

Senior Machine Learning Engineer

Lehi, UT · On-site +1

$144K - $233K/yr

Minimum Qualifications * 5+ years of software engineering or machine learning engineering ... Flexible and transparent culture with remote and hybrid work options, generous vacation time, and ...

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 ... Flexible and transparent culture with remote and hybrid work options, generous vacation time, and ...

Adobe

2027 Intern - Machine Learning Engineer

Lehi, UT · On-site +1

The Opportunity Adobe is looking for Machine Learning Engineer interns to work on some of the most impactful AI systems in the industry - from generative AI features and intelligent agents to search ...

Entrata

Senior Data Scientist

Lehi, UT · On-site +1

$133K - $213K/yr

Partner with machine learning engineers to move successful experiments into production. * Develop ... Flexible and transparent culture with remote and hybrid work options, generous vacation time, and ...

Entrata

Senior Data Scientist

Lehi, UT · On-site +1

$133K - $213K/yr

Partner with machine learning engineers to move successful experiments into production. * Develop ... Flexible and transparent culture with remote and hybrid work options, generous vacation time, and ...

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Remote Machine Learning Engineer information

See Salt Lake City, UT salary details

$30.4K

$124.4K

$186.9K

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

As of Sep 9, 2026, the average yearly pay for remote machine learning engineer in Salt Lake City, UT is $124,380.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,000.00 and $149,700.00 per year, depending on experience, location, and employer.

What is a remote machine learning engineer?

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.

What are the key skills and qualifications needed to thrive as a remote machine learning engineer?

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 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.

Are remote machine learning engineers still in demand?

Remote machine learning engineers are currently in high demand due to the growth of AI and data-driven technologies across industries. Skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch are highly sought after, and many companies continue to hire for remote roles in this field.

Can remote machine learning engineers work remotely?

Yes, remote machine learning engineers can work remotely, as many companies offer flexible work arrangements for this role. The position typically involves tasks such as data analysis, model development, and collaboration through online tools, making remote work feasible with strong communication skills and proficiency in programming languages like Python or frameworks like TensorFlow. However, some roles may require occasional on-site meetings or access to specialized hardware.

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

The most popular types of Machine Learning Engineer jobs in Salt Lake City, UT are:

What are popular job titles related to Remote Machine Learning Engineer jobs in Salt Lake City, UT?

For Remote Machine Learning Engineer jobs in Salt Lake City, UT, the most frequently searched job titles are:

What job categories do people searching Remote Machine Learning Engineer jobs in Salt Lake City, UT look for?

The top searched job categories for Remote Machine Learning Engineer jobs in Salt Lake City, UT are:

What cities near Salt Lake City, UT are hiring for Remote Machine Learning Engineer jobs?

Cities near Salt Lake City, UT with the most Remote Machine Learning Engineer job openings:

Remote Machine Learning Engineer jobs near you
Infographic showing various Remote Machine Learning Engineer job openings in Salt Lake City, UT as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $124,611 per year, or $59.9 per hour.

Senior Machine Learning Engineer

Lehi, UT • On-site, Remote

Entrata
Software Development • 1 - 5K employees
Learn more about Entrataexternal

$144K - $233K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 27 days ago

Entrata rating

7.9

Company rating: 7.9 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

130th of 247 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.

Following the launch of Forge, Entrata’s proprietary AI platform, we are looking for a Senior Machine Learning Engineer to drive the next generation of our applied AI capabilities. You will play a central role in fine-tuning Forge, optimizing domain-specific foundation models, and engineering robust ML pipelines that power intelligent automation for millions of residents and property managers worldwide.

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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