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Machine Learning Engineer Python Jobs in Lehi, UT

Waystar

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

... Machine Learning Engineering, with a strong focus on NLP. * Proven experience with Language Models (LMs), including model selection, fine-tuning, and deployment. * Strong proficiency in Python and ...

OC Tanner

Sr. Applied AI Engineer

Salt Lake City, UT · On-site

$101K - $138K/yr

Python / FastAPI microservices * LangChain / LangGraph * GraphQL / REST * PostgreSQL / Redis ... AWS Certified Machine Learning Engineer - Associate or equivalent * Cloud AI infrastructure ...

Octanner

Sr. Applied AI Engineer

Salt Lake City, UT

$101K - $138K/yr

Python / FastAPI microservices * LangChain / LangGraph * GraphQL / REST * PostgreSQL / Redis ... AWS Certified Machine Learning Engineer - Associate or equivalent * Cloud AI infrastructure ...

Pwc

AI Engineer

Salt Lake City, UT · On-site

$55K - $187K/yr

... AI Engineer, you will be at the forefront of transforming raw data into actionable insights ... machine learning models using Python and TensorFlow - Integrating data from diverse sources to ...

Pwc

AI Engineer

Salt Lake City, UT · On-site

$50K - $112K/yr

... AI Engineer, you will be at the forefront of transforming raw data into actionable insights ... machine learning models using Python and TensorFlow - Integrating data from various sources to ...

Autonomous Solutions

AI Infrastructure Engineer IV

Lehi, UT · On-site

$100K - $132K/yr

Strong programming skills in Python and/or C++, with experience supporting machine learning frameworks (TensorFlow, PyTorch, etc.). * Experience implementing CI/CD pipelines, MLOps practices, and ...

Autonomous Solutions

AI Infrastructure Engineer IV

Lehi, UT · On-site

$100K - $132K/yr

Strong programming skills in Python and/or C++, with experience supporting machine learning frameworks (TensorFlow, PyTorch, etc.). * Experience implementing CI/CD pipelines, MLOps practices, and ...

Autonomous Solutions

AI Infrastructure Engineer IV

Lehi, UT · On-site

$100K - $132K/yr

Strong programming skills in Python and/or C++, with experience supporting machine learning frameworks (TensorFlow, PyTorch, etc.). * Experience implementing CI/CD pipelines, MLOps practices, and ...

Waystar

Sr. Data Scientist

Lehi, UT · On-site

Required : • Complete familiarity with various statistical and machine learning techniques ... SQL Server) • Ability to code in 1+ general purpose programming language (C#, Java, etc.) • ...

Utah Community Credit Union

Data Engineer

Provo, UT

$108K - $130K/yr

... and machine learning initiatives across the credit union. Working closely with business ... Strong Python skills for data pipeline development and automation • Demonstrated experience ...

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All JobsMachine Learning Engineer Python JobsMachine Learning Engineer Python Jobs in Lehi, UT

Machine Learning Engineer Python information

See Lehi, UT salary details

$21.6K

$131.4K

$190.1K

How much do machine learning engineer python jobs pay per year?

As of Aug 6, 2026, the average yearly pay for machine learning engineer python in Lehi, UT is $131,392.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,700.00 and $154,400.00 per year, depending on experience, location, and employer.

What are some common challenges faced by machine learning engineers working with Python, and how can they be addressed?

Machine Learning Engineers using Python often encounter challenges such as managing large datasets, ensuring efficient model deployment, and maintaining reproducibility of experiments. Handling data pipelines and model versioning can be complex, especially as projects scale. To address these issues, engineers typically use tools like Pandas and Dask for data handling, Docker for containerization, and MLflow or DVC for tracking experiments and models. Collaborating closely with data engineers, software developers, and product teams is also essential to streamline workflows and ensure models are production-ready.

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

To thrive as a Machine Learning Engineer Python, you need a solid background in computer science, statistics, and mathematics, along with proficiency in Python programming and machine learning concepts. Familiarity with frameworks such as TensorFlow, PyTorch, Scikit-learn, and experience with cloud platforms or MLOps tools are highly valued, as are certifications like Google Professional Machine Learning Engineer. Strong problem-solving abilities, communication skills, and a collaborative mindset help set you apart in this field. These skills enable engineers to design, implement, and deploy effective machine learning solutions that address real-world challenges in dynamic, team-oriented environments.

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

AspectMachine Learning Engineer PythonData Scientist
Required CredentialsBachelor's/Master's in CS, Data Science, or related; Python skills; ML certificationsBachelor's/Master's in Statistics, CS, or related; Python/R skills; Data analysis certifications
Work EnvironmentDevelops scalable ML models, deploys algorithms, collaborates with engineering teamsAnalyzes data, builds models, interprets results, communicates insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles require Python proficiency and data skills, Machine Learning Engineers focus on building and deploying scalable ML models, whereas Data Scientists analyze data and generate insights. The roles often overlap but differ in their primary focus and responsibilities.

What is a machine learning engineer python?

A Machine Learning Engineer Python is a professional who uses the Python programming language to design, build, and deploy machine learning models and systems. They work with large datasets, develop algorithms, and use Python libraries such as TensorFlow, scikit-learn, and PyTorch to solve complex problems. Their responsibilities also include preprocessing data, training models, evaluating performance, and integrating solutions into production environments. Machine Learning Engineers often collaborate with data scientists, software engineers, and business stakeholders to create scalable and efficient machine learning applications.
Machine Learning Engineer Python jobs near you
Infographic showing various Machine Learning Engineer Python job openings in Lehi, UT as of June 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $131,392 per year, or $63.2 per hour.

Senior ML Engineer

Waystar

Lehi, UT • On-site

$98K - $134K/yr

Full-time

Medical, Retirement, PTO

Re-posted 5 days ago

Job description

ABOUT THIS POSITION
Job Description Summary
We are seeking a highly skilled and innovative Machine Learning Engineer with a passion for building robust, efficient, and domain-specific AI systems using Language Models (LMs) and agentic architectures. As a core member of the team, you will be instrumental in developing the entire ML pipeline, from sophisticated data extraction techniques to fine-tuning specialized LMs and orchestrating their interactions within a multi-agent framework.
This is a unique opportunity to apply state-of-the-art Generative AI and NLP techniques to a real-world, high-impact problem, leveraging the latest research in agentic AI and LMs to deliver economical and powerful solutions.
WHAT YOU'LL DO
    • Data Pipeline & Knowledge Base Construction:

    • Design, implement, and optimize robust pipelines for ingesting, parsing, and extracting structured information from complex documents (leveraging OCR, document layout analysis, Named Entity Recognition (NER), and Relationship Extraction (RE)).

    • Develop rich, nested JSON schemas for representing structured data and ensure scalable storage

    • Generate and manage high-quality vector embeddings for efficient retrieval-augmented generation (RAG) within a Vector Database.

    • Language Model (LM) Development & Fine-tuning:

    • Research, select, and experiment with appropriate open-source Language Models (Large & Small) (e.g., Phi-3, Mistral, Llama, Nemotron-H families) for specialized tasks.

    • Design and execute efficient fine-tuning strategies (e.g., LoRA, QLoRA, full fine-tuning) on curated, domain-specific datasets to achieve precise performance for tasks like coverage determination, code lookups, and policy rule application.

    • Explore and implement knowledge distillation techniques to transfer capabilities from larger models to smaller, more efficient LMs.

    • Agentic System Design & Implementation:

    • Build and maintain the core agentic framework, including the orchestrator that intelligently routes queries and coordinates interactions between various specialized LM tools.

    • Develop and integrate "tools" (specialized LMs and external APIs) that perform atomic medical necessity tasks, ensuring strict behavioral alignment and structured outputs.

    • MLOps & Deployment:

    • Deploy, manage, and monitor LMs and agentic components on Google Cloud Platform (GCP) using services like Vertex AI, GKE, Cloud Functions, and Cloud Run.

    • Implement robust MLOps practices for continuous integration, continuous delivery (CI/CD), model versioning, and performance monitoring (latency, throughput, accuracy).

    • Continuous Improvement & Research:

    • Establish effective feedback loops from end-user interactions and system logs to identify areas for model improvement.

    • Curate and expand training datasets, ensuring data privacy (PHI/PII masking) and legal compliance.

    • Stay abreast of the latest research in LMs, agentic AI, NLP, and document understanding, applying relevant advancements to our system.

    • Collaboration:

    • Work closely with subject matter experts, product managers, and other engineers to translate complex requirements into technical solutions and evaluate system performance.

    • Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.

    • 3+ years of professional experience in Machine Learning Engineering, with a strong focus on NLP.

    • Proven experience with Language Models (LMs), including model selection, fine-tuning, and deployment.

    • Strong proficiency in Python and familiarity with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers).

    • Solid understanding and hands-on experience with core NLP techniques and architectures, especially Transformers.

    • Experience with cloud platforms, particularly Google Cloud Platform (GCP), including services like Vertex AI, Cloud Storage, and compute services.

    • Familiarity with MLOps principles and tools for model serving, monitoring, and pipeline automation.

    • Excellent problem-solving skills, attention to detail, and ability to work independently and collaboratively.

    • Active use of artificial intelligence (AI) tools and techniques to enhance performance, drive innovation, and improve decision-making across business functions.

    • Ability to leverage AI tools and platforms to streamline workflows, improve decision-making, and drive innovation.

    • Curiosity and adaptability in exploring emerging AI technologies, with a mindset for continuous learning and experimentation.

WHAT YOU'LL NEED
  • What Will Make You Stand Out (Preferred Qualifications):
    • Hands-on experience building or contributing to agentic AI systems or multi-agent frameworks.

    • Direct experience with document processing technologies such as OCR, layout parsing, Document AI, or custom information extraction from unstructured text.

    • Experience with Vector Databases (e.g., pgvector, Pinecone, Weaviate, Qdrant) and RAG architectures.

    • Exposure to the healthcare domain, particularly understanding medical terminology, CPT/ICD codes, or regulatory documents.

ABOUT WAYSTAR
Through a smart platform and better experience, Waystar helps providers simplify healthcare payments and yield powerful results throughout the complete revenue cycle.
Waystar's healthcare payments platform combines innovative, cloud-based technology, robust data, and unparalleled client support to streamline workflows and improve financials so providers can focus on what matters most: their patients and communities. Waystar is trusted by 1M+ providers, 1K+ hospitals and health systems, and is connected to over 5K commercial and Medicaid/Medicare payers. We are deeply committed to living out our organizational values: honesty; kindness; passion; curiosity; fanatical focus; best work, always; making it happen; and joyful, optimistic & fun.
Waystar products have won multiple Best in KLAS® or Category Leader awards since 2010 and earned multiple #1 rankings from Black Book™ surveys since 2012. The Waystar platform supports more than 500,000 providers, 1,000 health systems and hospitals, and 5,000 payers and health plans. For more information, visit waystar.com or follow @Waystar on Twitter.
WAYSTAR PERKS
  • Competitive total rewards (base salary + bonus, if applicable)
  • Customizable benefits package (3 medical plans with Health Saving Account company match)
  • We offer generous paid time off for our non-exempt team members, starting with 3 weeks + 13 paid holidays, including 2 personal floating holidays. We also offer flexible time off for our exempt team members + 13 paid holidays
  • Paid parental leave (including maternity + paternity leave)
  • Education assistance opportunities and free LinkedIn Learning access
  • Free mental health and family planning programs, including adoption assistance and fertility support
  • 401(K) program with company match
  • Pet insurance
  • Employee resource groups

Waystar is proud to be an equal opportunity workplace. We celebrate, value, and support diversity and inclusion. Qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, marital status, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.
This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

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