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Entry Level Machine Learning Engineer Jobs in Eagle Mountain, UT

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 ...

Ancestry

Machine Learning Engineer, Co-op

Lehi, UT · Remote

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 ...

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 ...

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 ...

Waystar

Sr. Data Scientist

Lehi, UT · On-site

Responsibilities : • Works closely with Application Engineering, Product Management, and Operational teams in designing, experimenting-with, and implementing machine learning and analytical systems ...

Patientco

Data Scientist

Lehi, UT · On-site

Worksclosely withApplication Engineering,ProductManagement, and Operationalteams in designing, experimenting-with,and implementing machine learning and analytical systems applied to design ...

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Entry Level Machine Learning Engineer information

See Eagle Mountain, UT salary details

$29.4K

$68K

$115.7K

How much do entry level machine learning engineer jobs pay per year?

As of Aug 5, 2026, the average yearly pay for entry level machine learning engineer in Eagle Mountain, UT is $68,025.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,500.00 and $77,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an entry level machine learning engineer?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are some typical projects or tasks an entry level machine learning engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What is an entry level machine learning engineer?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are popular job titles related to Entry Level Machine Learning Engineer jobs in Eagle Mountain, UT? For Entry Level Machine Learning Engineer jobs in Eagle Mountain, UT, the most frequently searched job titles are:
What job categories do people searching Entry Level Machine Learning Engineer jobs in Eagle Mountain, UT look for? The top searched job categories for Entry Level Machine Learning Engineer jobs in Eagle Mountain, UT are:
What cities near Eagle Mountain, UT are hiring for Entry Level Machine Learning Engineer jobs? Cities near Eagle Mountain, UT with the most Entry Level Machine Learning Engineer job openings:
Entry Level Machine Learning Engineer jobs near you
Infographic showing various Entry Level Machine Learning Engineer job openings in Eagle Mountain, UT as of July 2026, with employment types broken down into 1% Locum Tenens, 85% Full Time, 12% Part Time, and 2% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $68,025 per year, or $32.7 per hour.

Senior Machine Learning Engineer

NICE

Sandy, UT • Hybrid

$99K - $136K/yr

Other

Posted 22 days ago

Job description

So, what's the role all about?

NiCE is looking for a Senior Machine Learning Engineer to join NiCE Labs Research (NLR), a team dedicated to model expertise and agent architecture for the Cognigy platform. 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 languages.

This role is primarily concerned with rigorous measurement: designing test suites, running comparative evaluations, and producing actionable recommendations on model selection and configuration.

The Senior Machine Learning Engineer monitors the rapidly evolving speech AI landscape to identify state-of-the-art transcription and speech-to-speech models for evaluation. You will design and maintain a speech-oriented test suite that covers quality, cost, and latency, and develop techniques to optimize model usage for operational deployment.

This role requires deep expertise in speech AI systems, strong quantitative skills, and the discipline to produce reliable, reproducible evaluation results.

How will you make an impact?

  • Design and maintain a speech-oriented test suite covering quality, cost, and latency across dozens of languages.
  • Monitor the industry for new state-of-the-art transcription and speech-to-speech models to evaluate.
  • Design and evaluate techniques to optimize speech model usage for operational deployment.
  • Produce clear, quantitative evaluation reports and model recommendations for technical and non-technical stakeholders.
  • Contribute to the broader model evaluation framework maintained by the NLR team.
  • Stay informed of advances in speech AI, including transcription, text-to-speech, and speech-to-speech technologies.

Have you got what it takes?

  • MS in computer science, electrical engineering, computational linguistics, or a related field with a focus on speech or audio processing.
  • Three or more years of hands-on experience with speech AI systems, including ASR, TTS, or speech-to-speech models.
  • Experience designing evaluation methodologies or test suites for AI systems.
  • Strong quantitative and analytical skills, with experience producing rigorous benchmark results.
  • LoRA/PEFT for speech models, inference optimization (quantization, SGLang/vLLM serving for audio, distillation), experience with at least one open-source TTS family
  • GPU cost modeling
  • Proficiency in Python and familiarity with speech processing libraries and tools.
  • Experience with cloud-based infrastructure (AWS, Azure, or GCP).
  • Ability to develop and maintain good working relationships with cross-functional teams.
  • Ability to clearly communicate and present to internal and external stakeholders.

You will have an advantage if you have:

  • Experience evaluating speech models across multiple languages.
  • Familiarity with multi-cloud deployment across AWS, Azure, and Google Cloud.
  • Experience with model optimization techniques for speech systems, such as latency reduction or cost optimization.
  • Exposure to contact center or conversational AI platforms.
  • Experience working on international, globe-spanning teams.

 

What's in it for you?

Join an ever-growing, market disrupting, global company where the teams - comprised of the best of the best - work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NiCE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NICEr!

Enjoy NiCE-FLEX!

At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

 

Requisition ID: 11422

Reporting into: Director, Engineering, AI Research, NiCE Labs

Role Type: Individual Contributor

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