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Manager Remote Machine Learning Engineer Jobs in Herriman, UT

Senior Machine Learning Engineer

Lehi, UT · On-site +1

$144K - $233K/yr

This role will focus on adapting and fine-tuning foundation models for property management use ... Flexible and transparent culture with remote and hybrid work options, generous vacation time, and ...

Senior Machine Learning Engineer

Lehi, UT · On-site +1

$144K - $233K/yr

This role will focus on adapting and fine-tuning foundation models for property management use ... Flexible and transparent culture with remote and hybrid work options, generous vacation time, and ...

The Opportunity Adobe is looking for Machine Learning Engineer interns to work on some of the most ... Managers will determine the frequency you need to go into the office to meet priorities. What You ...

New

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 ...

Senior Data Scientist

Lehi, UT · On-site +1

$133K - $213K/yr

... management technology. Today, we power the industry's most essential operating system, serving ... Partner with machine learning engineers to move successful experiments into production. * Develop ...

Senior Data Scientist

Lehi, UT · On-site +1

$133K - $213K/yr

... management technology. Today, we power the industry's most essential operating system, serving ... Partner with machine learning engineers to move successful experiments into production. * Develop ...

Act as the go-between for developers and business systems admins, reaching out to the business to ... and be comfortable learning new systems on the fly. * Hands-On AI Experience: Demonstrated ...

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Manager Remote Machine Learning Engineer information

See Herriman, UT salary details

$28.9K

$65.1K

$109.5K

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

As of Sep 3, 2026, the average yearly pay for manager remote machine learning engineer in Herriman, UT is $65,054.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,300.00 and $70,600.00 per year, depending on experience, location, and employer.

What is a manager remote machine learning engineer?

A Manager Remote Machine Learning Engineer is a leadership role responsible for overseeing a team of machine learning engineers who work remotely. They manage the development, deployment, and optimization of machine learning models and ensure that projects align with organizational goals. In addition to technical expertise, this manager focuses on remote team collaboration, communication, and productivity. They often coordinate workflows, mentor team members, and act as a bridge between technical teams and business stakeholders.

How does a manager remote machine learning engineer typically balance team leadership with hands-on technical responsibilities?

A Manager Remote Machine Learning Engineer often splits time between leading and mentoring a distributed team and actively contributing to machine learning projects. While overseeing project timelines, conducting code reviews, and setting technical direction are key leadership tasks, managers also stay involved in model development and troubleshooting to maintain technical expertise. Effective communication and clear documentation are crucial, as remote teams rely on these to collaborate efficiently across different time zones. Balancing these responsibilities requires strong organizational skills and the ability to prioritize both people management and technical deliverables.

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

To thrive as a Manager Remote Machine Learning Engineer, strong expertise in machine learning algorithms, programming (Python, R), and a degree in computer science or a related field are essential, along with proven leadership experience. Familiarity with cloud platforms (AWS, Azure, GCP), ML frameworks (TensorFlow, PyTorch), and project management tools is typically required, as well as certifications such as AWS Certified Machine Learning or Google Professional Machine Learning Engineer. Outstanding communication, team leadership, and problem-solving skills help foster collaboration and drive remote teams toward project goals. These capabilities are vital for effectively managing distributed teams, delivering robust AI solutions, and ensuring project success in a remote environment.

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

AspectManager Remote Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience in ML engineeringBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentRemote, collaborative teams, focus on ML model deploymentRemote or on-site, data analysis, model development, research
Employer & Industry UsageTech companies, AI startups, large enterprisesTech, finance, healthcare, research institutions
Search & Comparison IntentUnderstanding managerial roles in ML teamsData analysis, modeling, research tasks

The Manager Remote Machine Learning Engineer oversees ML projects and teams, focusing on deployment and management, while Data Scientists primarily analyze data and develop models. Both roles require strong technical skills, but the manager role emphasizes leadership and project oversight.

Can a manager remote machine learning engineer work remotely?

Yes, a manager remote machine learning engineer can work remotely, as many companies offer remote positions for this role. Success in remote work often depends on strong communication skills, familiarity with collaboration tools, and the ability to manage projects independently.

What job categories do people searching Manager Remote Machine Learning Engineer jobs in Herriman, UT look for?

The top searched job categories for Manager Remote Machine Learning Engineer jobs in Herriman, UT are:

Infographic showing various Manager Remote Machine Learning Engineer job openings in Herriman, UT as of August 2026, with employment types broken down into 90% Full Time, 9% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $65,054 per year, or $31.3 per hour.

Senior Machine Learning Engineer

Entrata

Lehi, UT • On-site, Remote

$144K - $233K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 21 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.

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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