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Privacy Preserving Machine Learning Jobs in Utah

Crew Career Center

Senior ML Engineer

Lehi, UT

$98K - $134K/yr

ABOUT THIS POSITION Summary We are seeking a highly skilled and innovative Machine Learning ... Curate and expand training datasets, ensuring data privacy (PHI/PII masking) and legal compliance.

Patientco

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

ABOUT THIS POSITION Summary We are seeking a highly skilled and innovative Machine Learning ... Curate and expand training datasets, ensuring data privacy (PHI/PII masking) and legal compliance.

Utah Community Credit Union

Data Engineer

Provo, UT · On-site

$108K - $130K/yr

... and machine learning initiatives across the credit union. Working closely with business ... data privacy standards • Partner with the IT security team to enforce data access controls ...

Patientco

VP, Data Sciences

Lehi, UT · On-site

... privacy, and compliance with relevant regulations (e.g., HIPAA, GDPR, CCPA). Data Platform ... Driving the development and deployment of advanced analytical models, machine learning algorithms ...

Waystar

VP, Data Sciences

Lehi, UT · On-site

... privacy, and compliance with relevant regulations (e.g., HIPAA, GDPR, CCPA). * **Data Platform ... Driving the development and deployment of advanced analytical models, machine learning algorithms ...

Crew Career Center

VP, Data Sciences

Lehi, UT · On-site

... privacy, and compliance with relevant regulations (e.g., HIPAA, GDPR, CCPA). Data Platform ... Driving the development and deployment of advanced analytical models, machine learning algorithms ...

Omnicom

Data Analyst

Salt Lake City, UT · On-site

Preferred, but not required: - Interest or background in machine learning / predictive modelling ... Link to Recruitment Privacy Notice: For US Job Seekers: It is the policy of Omnicom and any of its ...

Omnicom

Data Analyst

Salt Lake City, UT · Hybrid

Preferred, but not required: - Interest or background in machine learning / predictive modelling ... Link to Recruitment Privacy Notice: For US Job Seekers: It is the policy of Omnicom and any of its ...

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All JobsPrivacy Preserving Machine Learning JobsPrivacy Preserving Machine Learning Jobs in Utah

Privacy Preserving Machine Learning information

What is privacy preserving machine learning?

Privacy preserving machine learning refers to techniques and methods that allow data analysis and model training while protecting sensitive information. This field focuses on ensuring that personal or confidential data is not exposed or compromised during the development and deployment of machine learning models. Approaches such as federated learning, differential privacy, and homomorphic encryption are commonly used. These methods enable organizations to leverage data for insights and predictions without violating privacy regulations or risking data breaches. Privacy preserving machine learning is especially important in industries like healthcare, finance, and any sector handling personal data.

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

To thrive as a Privacy Preserving Machine Learning Engineer, you need a strong background in machine learning, data privacy techniques (such as differential privacy or federated learning), and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow Privacy, PySyft, and privacy-enhancing technologies, along with certifications in data security or privacy, are often required. Strong problem-solving abilities, meticulous attention to detail, and the ability to communicate complex technical concepts clearly set top professionals apart. These skills ensure the development of robust machine learning models that protect sensitive data while delivering valuable insights, maintaining compliance and trust.

What are some common challenges faced by professionals working in privacy preserving machine learning roles?

Professionals in Privacy Preserving Machine Learning often encounter challenges such as balancing model accuracy with strict privacy requirements, selecting appropriate privacy-preserving techniques (like differential privacy or federated learning), and ensuring compliance with evolving data protection regulations. Collaborative projects may also involve coordinating with legal, data security, and software engineering teams to implement robust solutions. Additionally, staying updated with the latest research and adapting to new threats or vulnerabilities is a continuous part of the role.

What is the difference between Privacy Preserving Machine Learning vs Data Scientist?

AspectPrivacy Preserving Machine LearningData Scientist
Required CredentialsTypically requires knowledge of machine learning, data privacy, and security certificationsRequires degrees in data science, statistics, or related fields; certifications like Certified Data Scientist are common
Work EnvironmentWorks in research, development, and implementation of privacy-focused ML models, often in tech or finance sectorsAnalyzes data, builds models, and provides insights across various industries including marketing, finance, and healthcare
Employer & Industry UsageUsed by organizations prioritizing data privacy, such as healthcare, finance, and tech companiesEmployed across diverse sectors for data analysis, predictive modeling, and decision support

Privacy Preserving Machine Learning focuses on developing models that protect data privacy during training and inference, while Data Scientists analyze and interpret data to generate insights. Both roles require strong analytical skills, but Privacy Preserving Machine Learning emphasizes security and privacy techniques, whereas Data Scientists focus on data analysis and modeling.

What are popular job titles related to Privacy Preserving Machine Learning jobs in Utah?

For Privacy Preserving Machine Learning jobs in Utah, the most frequently searched job titles are:

What job categories do people searching Privacy Preserving Machine Learning jobs in Utah look for?

The top searched job categories for Privacy Preserving Machine Learning jobs in Utah are:

What cities in Utah are hiring for Privacy Preserving Machine Learning jobs?

Cities in Utah with the most Privacy Preserving Machine Learning job openings:

Privacy Preserving Machine Learning jobs near you
Infographic showing various Privacy Preserving Machine Learning job openings in Utah as of June 2026, with employment types broken down into 74% Full Time, 23% Part Time, and 3% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution.

Senior ML Engineer

Crew Career Center

Lehi, UT

$98K - $134K/yr

Full-time

Medical, Retirement, PTO

Re-posted 3 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.comor follow @Waystaron 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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