1

Machine Learning Engineer Opt Jobs in Utah (NOW HIRING)

AI Engineer

Saint George, UT · On-site

$50K - $90K/yr

About The Role As an AI Engineer, you will design, build, and deploy sophisticated AI solutions ... Collaborating closely with cross-functional teams, you will develop and optimize machine learning ...

About The Role As an AI Engineer, you will design, build, and deploy sophisticated AI solutions ... Collaborating closely with cross-functional teams, you will develop and optimize machine learning ...

Extractive Metallurgist

Moab, UT · On-site

$100K - $160K/yr

You'll work closely with operations, engineers, machine learning experts, and data scientists to develop innovative solutions that improve efficiency, recovery, and throughput across our projects.

This is an opportunity to work closely with data scientists, engineers, product leaders, and healthcare experts to design, build, and deploy production machine learning models and scalable data ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

AI Infrastructure Engineer IV

Lehi, UT · On-site

$100.90K - $132.40K/yr

As an AI Infrastructure Engineer IV , you will play a critical role in designing, building, and maintaining the systems that power our AI and machine learning capabilities. You will ensure our ...

AI Infrastructure Engineer IV

Mendon, UT · On-site

$93.70K - $122.90K/yr

As an AI Infrastructure Engineer IV , you will play a critical role in designing, building, and maintaining the systems that power our AI and machine learning capabilities. You will ensure our ...

AI Infrastructure Engineer IV

Lehi, UT · On-site

$100.90K - $132.40K/yr

As an AI Infrastructure Engineer IV , you will play a critical role in designing, building, and maintaining the systems that power our AI and machine learning capabilities. You will ensure our ...

AI Infrastructure Engineer IV

Mendon, UT · On-site

$93.70K - $122.90K/yr

As an AI Infrastructure Engineer IV , you will play a critical role in designing, building, and maintaining the systems that power our AI and machine learning capabilities. You will ensure our ...

AI Infrastructure Engineer IV

Lehi, UT

$100.90K - $132.40K/yr

As an AI Infrastructure Engineer IV , you will play a critical role in designing, building, and maintaining the systems that power our AI and machine learning capabilities. You will ensure our ...

AI/ML Engineer

Sandy, UT · On-site

$108.80K - $130.70K/yr

... machine-learning models or AI services aligned with business needs • Support deployment of AI ... programming skills or similar languages • Experience with machine-learning libraries such as ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Sr. Data Engineer

Draper, UT

$107K - $128.50K/yr

Essential Job Duties As a Senior Data Engineer, you will play a key role in designing, building ... Design, build, and operationalize machine learning pipelines for training, validation, deployment ...

Responsibilities : • Works closely with other Data Scientists, Application Engineering, Product Management, and Operational teams in designing, experimenting with, and implementing machine learning ...

next page

Showing results 1-20

Machine Learning Engineer Opt information

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

What cities in Utah are hiring for Machine Learning Engineer Opt jobs? Cities in Utah with the most Machine Learning Engineer Opt job openings:
AI Engineer / Applied Data Scientist

AI Engineer / Applied Data Scientist

Kforce Technology Staffing

Draper, UT

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago


Job description

RESPONSIBILITIES:
Kforce has a client that is seeking an AI Engineer/Applied Data Scientist in Draper, UT.
Overview:
In this role, you will operate at the intersection of AI engineering and applied data science. You will design, build, and deploy machine learning, generative AI, and agentic AI systems that power real-world products and decision-making at scale.
You will work end-to-end-from data exploration and modeling through production deployment-partnering closely with product, engineering, and business stakeholders to deliver measurable, reliable, and responsible AI outcomes.
Duties Include:
* Design, build, and optimize machine learning models, including classification, regression, clustering, and recommendation systems
* Develop and productionize LLM-based solutions, including prompt engineering, retrieval-augmented generation (RAG) pipelines, fine-tuning, and multimodal models
* Build and orchestrate agentic AI workflows (LangGraph or similar), including tool usage, decision logic, and long-running agent execution
* Leverage AI-assisted development tools (e.g., Claude Code or similar) to accelerate software development, testing, and refactoring while maintaining high standards of quality and correctness
* Design and implement modular sub-agents and reusable tools, applying strong software engineering and data science principles across the agent lifecycle (design, build, evaluate, deploy, and iterate)
* Apply embeddings and vector search techniques to enable NLP, semantic search, and retrieval use cases
* Process and analyze large-scale datasets using Python (pandas, scikit-learn, PySpark) and SQL
* Implement MLOps best practices, including CI/CD pipelines, model versioning, monitoring, evaluation, and reproducibility
* Evaluate model and LLM performance in production using offline, online, and incremental evaluation strategies
* Translate complex analytical results into clear, actionable insights for both technical and non-technical stakeholders
REQUIREMENTS:
* Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field
* 2+ years of hands-on experience in data science, machine learning engineering, or applied AI within a fast-paced, production-oriented environment
* Advanced proficiency in Python, including experience with pandas, scikit-learn, and PySpark
* Strong SQL skills for large-scale data analysis and feature engineering
* Proven experience building, tuning, and evaluating machine learning models, with a solid understanding of evaluation metrics and tradeoffs
* Experience with vector embeddings, similarity search, and retrieval pipelines
* Practical experience with LLMs, including prompt engineering, API/SDK integration, multimodal models, and fine-tuning approaches
* Hands-on experience with agentic development frameworks (LangGraph preferred or equivalent), including orchestration patterns, sub-agents, and tool integration
* Experience using AI-assisted (-agentic coding-) development tools, with strong engineering judgment around correctness, testing, and maintainability
* Understanding of the agentic software lifecycle, including evaluation, observability, failure modes, and iterative improvement in production environments
* Familiarity with responsible AI principles, including bias, fairness, and governance in deployed systems
* Ability to translate business problems into scalable AI/ML solutions and communicate effectively across technical and non-technical audiences
* Experience working cross-functionally in Agile environments, with clear and thorough documentation practices
* Familiarity with model deployment and MLOps practices, including CI/CD, monitoring, and reproducibility
Nice to Have:
* Experience operating and scaling agentic AI systems in production environments
* Background in recommendation systems, optimization, or decision intelligence
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
By clicking ?Apply Today? you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.