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Manager Remote Machine Learning Engineer Jobs in Herriman, UT

As a Machine Learning Engineer Co-Op on the MLE team, you will work on integrating ML models and Generative AI (GenAI) models, enabling ML/LLM-powered applications, and developing AI agents using ...

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 ...

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 ...

New

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 ...

Project Manager (Remote)

Sandy, UT · On-site +1

$90K - $100K/yr

About the Role FMG's Product Operations team sits at the intersection of Product, Engineering, and the business - and we're growing. We're looking for a Project Manager who thrives in the complexity ...

Project Manager (Remote)

Midvale, UT · Remote

$90K - $100K/yr

About the Role FMG's Product Operations team sits at the intersection of Product, Engineering, and the business -- and we're growing. We're looking for a Project Manager who thrives in the complexity ...

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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 Jul 23, 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.

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.

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.

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 popular job titles related to Manager Remote Machine Learning Engineer jobs in Herriman, UT? For Manager Remote Machine Learning Engineer jobs in Herriman, UT, the most frequently searched job titles are:
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:
Machine Learning Engineer, Co-op

Machine Learning Engineer, Co-op

Ancestry

Lehi, UT • Remote

Part-time

Posted 14 days ago


Job description

About Ancestry:


When you join Ancestry, you join a human-centered company where every person’s story is important. Ancestry®, the global leader in family history, connects everyone with their past so they can discover, preserve, and share their unique family stories. With our unparalleled collection of more than 65 billion records, over 3.5 million subscribers, and over 27 million people in our growing DNA network, customers can discover their family story and gain a new level of understanding about their lives. Over the past 40 years, we’ve built trusted relationships with millions of people who have chosen us as the platform for discovering, preserving, and sharing the most important information about themselves and their families.
We are committed to our location flexible work approach, allowing you to choose to work in the nearest office, from your home, or a hybrid of both (subject to location restrictions and roles that are required to be in the office- see the full list of eligible US locations HERE). We will continue to hire and promote beyond the boundaries of our office locations, to enable broadened possibilities for employee diversity.
Together, we work every day to foster a work environment that's inclusive as well as diverse, and where our people can be themselves. Every idea and perspective is valued so that our products and services reflect the global and diverse clients we serve. 
Ancestry encourages applications from minorities, women, the disabled, protected veterans and all other qualified applicants. Passionate about dedicating your work to enriching people’s lives? Join the curious.

Ancestry seeks an exceptional, passionate, and highly motivated Machine Learning Engineer Co-Op to join our MLE team this summer. The MLE team is responsible for developing, deploying, fine-tuning and optimizing machine learning models and LLMs to enhance customer experiences, improve internal workflows, and drive business impact. We collaborate closely with data scientists, engineers, and product teams to build scalable and efficient ML solutions that power critical features across our platform. As a Machine Learning Engineer Co-Op on the MLE team, you will work on integrating ML models and Generative AI (GenAI) models, enabling ML/LLM-powered applications, and developing AI agents using agentic frameworks. You will contribute to optimizing model inference, automating ML workflows, and building intelligent AI-driven solutions to improve decision-making and user engagement. This is a part-time, work-study-based opportunity for active students in master's and PhD programs.
What You Will Do:

  • Develop and deploy machine learning and large language models.

  • Build and optimize AI agents to enhance automation and decision-making.

  • Optimize model inference speed, storage efficiency, and scalability for real-world applications.

  • Develop pipelines and MLOps workflows to streamline model training, evaluation, and deployment.

  • Contribute to ML, LLMs, agent evaluation and monitoring platform.

  • Experiment with new ML, LLM, and Agent technologies.

Who You Are:

  • Currently pursuing an advanced degree (Master's or PhD preferred) in Computer Science, Data Science, Statistics, Mathematics, Linguistics, Engineering or related quantitative field with a strong data focus.

  • Proficient in Python and familiar with ML libraries such as TensorFlow, PyTorch or Scikit-learn.

  • Experience with GenAI, LLMs, and agentic frameworks (LangChain, AutoGen).

  • Strong problem-solving skills, with the ability to write clean, efficient, and scalable code.

  • Strong written and verbal communication skills

  • Curiosity and go-getter attitude

  • Experience with cloud platforms, ML development tools, and ML deployment tools.

  • Nice to have: Familiarity NodeJS or Java

  • Nice to have: Familiarity with LLM fine-tuning, retrieval-augmented generation (RAG), vector databases (FAISS, Pinecone, OpenSearch), LLM optimization, VLLM library, HuggingFace library or reinforcement learning techniques.

Additional Information:

Ancestry is an Equal Opportunity Employer that makes employment decisions without regard to race, color, religious creed, national origin, ancestry, sex, pregnancy, sexual orientation, gender, gender identity, gender expression, age, mental or physical disability, medical condition, military or veteran status, citizenship, marital status, genetic information, or any other characteristic protected by applicable law. In addition, Ancestry will provide reasonable accommodations for qualified individuals with disabilities.

All job offers are contingent on a background check screen that complies with applicable law. For candidates who live in San Francisco, CA, pursuant to the San Francisco Fair Chance Ordinance, Ancestry will consider for employment qualified applicants with arrest and conviction records.

Ancestry is not accepting unsolicited assistance from search firms for this employment opportunity. All resumes submitted by search firms to any employee at Ancestry via-email, the Internet or in any form and/or method without a valid written search agreement in place for this position will be deemed the sole property of Ancestry. No fee will be paid in the event the candidate is hired by Ancestry as a result of the referral or through other means.