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Remote Google Machine Learning Engineer Jobs in Salt Lake City, 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 ...

Senior DevOps Engineer (US REMOTE)

West Valley City, UT · Remote

$140K - $170K/yr

  • Medical

  • Dental

  • Retirement

... s Full-Stack Engineer with expertise in IaC (Terraform), Helm, MySQL, Kubernetes, and CI/CD ... Experience with AI/machine learning technologies is strongly preferred. * Familiarity with TCP/IP ...

Sr. Software Engineer

Salt Lake City, UT · Remote

$125K - $165K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

Experience with machine learning or generative AI prompt engineering * Caching/NoSQL datastores ... Remote-friendly policy * Medical/vision/dental insurance * Life, short-term disability, and ...

Lead Data Scientist

Holladay, UT · On-site +1

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... machine learning and data engineering to develop scalable solutions. - Identify areas where resources fall short of needs and provide thoughtful and sustainable solutions to benefit the team - Be a ...

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

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Showing results 1-20

Remote Google Machine Learning Engineer information

See Salt Lake City, UT salary details

$30.5K

$124.6K

$187.3K

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

As of Aug 15, 2026, the average yearly pay for remote google machine learning engineer in Salt Lake City, UT is $124,611.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,200.00 and $150,000.00 per year, depending on experience, location, and employer.

What is a remote Google machine learning engineer?

A Remote Google Machine Learning Engineer is a professional who designs, builds, and deploys machine learning models and artificial intelligence solutions, often using Google Cloud technologies, while working from a remote location. These engineers collaborate with cross-functional teams to solve complex business problems, optimize data pipelines, and improve model performance. Their responsibilities typically include data preprocessing, model selection, training, evaluation, and deployment, all while ensuring scalability and security. Working remotely allows them to contribute to projects from anywhere, leveraging cloud-based tools and collaboration platforms.

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

To thrive as a Remote Google Machine Learning Engineer, you need a strong background in computer science, mathematics, and machine learning algorithms, typically supported by a relevant degree and experience in building scalable models. Proficiency with tools such as TensorFlow, Python, Google Cloud Platform (GCP), and familiarity with distributed systems is essential. Excellent problem-solving, communication, and self-management skills are crucial for effective remote collaboration and innovation. These capabilities enable engineers to deliver impactful machine learning solutions while seamlessly integrating with global Google teams.

How do remote Google machine learning engineers typically collaborate with cross-functional teams while working from different locations?

Remote Google Machine Learning Engineers often use a combination of video conferencing, cloud-based collaboration tools, and shared code repositories to work closely with data scientists, product managers, and software engineers. Regular stand-up meetings, sprint planning sessions, and detailed documentation help ensure everyone is aligned and project milestones are met. Despite being remote, engineers are encouraged to proactively communicate progress, share insights, and participate in code reviews to maintain a strong team dynamic and drive successful project outcomes.

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

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

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

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

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

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

Infographic showing various Remote Google Machine Learning Engineer job openings in Salt Lake City, UT as of August 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 100% Remote job distribution, with an average salary of $124,611 per year, or $59.9 per hour.

Machine Learning Engineer, Co-op

Ancestry

Lehi, UT • Remote

Part-time

Re-posted 7 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.