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Machine Learning Engineer Quantization Jobs in Utah

Senior ML Engineer

Lehi, UT ยท On-site

$98K - $134K/yr

ABOUT THIS POSITION 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 ...

Sr. Applied AI Engineer

Salt Lake City, UT ยท On-site

$101K - $138K/yr

AWS Certified Machine Learning Engineer - Associate or equivalent * Cloud AI infrastructure management using AWS services and Terraform * AI observability experience with OpenTelemetry, Langfuse, or ...

Sr. Applied AI Engineer

Salt Lake City, UT

$101K - $138K/yr

AWS Certified Machine Learning Engineer - Associate or equivalent * Cloud AI infrastructure management using AWS services and Terraform * AI observability experience with OpenTelemetry, Langfuse, or ...

Data Scientists

Salt Lake City, UT ยท On-site

$75K - $105K/yr

Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make ...

Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make ...

AI Solutions Engineering Delivery Lead

Salt Lake City, UT ยท On-site

$99K - $130K/yr

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 Engineer

Saint George, UT ยท 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 ...

Senior AI/ML Engineer

Draper, UT ยท On-site

$100 - $130/hr

You'll be a Senior AI/ML Engineer, designing and building AI-powered features like chatbots and ... Expertise in AI, machine learning, and natural language processing (NLP). * Strong communication ...

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 ...

Understanding of machine learning fundamentals and Generative AI concepts * Hands-on experience working with Large Language Models (LLMs), including prompt engineering techniques * Experience ...

Data Engineer

Salt Lake City, UT ยท On-site

$109K - $131K/yr

Data Engineer We are seeking a high skilled and motivated Sr. Data Engineer to join our team. The ... Machine Learning Support: * Collaborate on the development and deployment of machine learning ...

New

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 ยท On-site

$100K - $132K/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 ยท On-site

$93K - $122K/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 compute ...

Showing results 41-60

Machine Learning Engineer Quantization information

What are some common challenges machine learning engineers face when implementing quantization techniques in production models?

Machine Learning Engineers working on quantization often encounter challenges such as balancing reduced model size and computational efficiency with maintaining acceptable accuracy levels. Adapting quantization methods to different hardware platforms can also require significant testing and optimization. Additionally, engineers must frequently address compatibility issues with existing deployment pipelines and ensure that quantization-aware training is properly integrated to minimize performance degradation. Collaboration with hardware and software teams is essential to streamline deployment and achieve optimal results.

What are the key skills and qualifications needed to thrive as a machine learning engineer quantization, and why are they important?

To thrive as a Machine Learning Engineer Quantization, you need a solid background in machine learning, deep learning, and computer science, typically supported by a degree in a related field. Familiarity with quantization techniques, frameworks such as TensorFlow Lite or PyTorch, and experience with hardware accelerators are crucial. Strong problem-solving skills, attention to detail, and effective collaboration set top performers apart. These capabilities are vital for efficiently deploying high-performing models on resource-constrained devices and ensuring scalable, real-world AI solutions.

What does a machine learning engineer quantization do?

A Machine Learning Engineer specializing in quantization focuses on optimizing machine learning models by reducing their size and computational requirements without significantly sacrificing accuracy. This involves converting model parameters and computations from high-precision formats (like 32-bit floating point) to lower-precision formats (such as 8-bit integers). Quantization enables faster inference, lower memory usage, and allows models to run efficiently on edge devices and mobile platforms. These engineers work closely with data scientists and hardware teams to implement, test, and validate quantized models in production environments.

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

AspectMachine Learning Engineer QuantizationData Scientist
Required CredentialsBachelor's or master's in CS, ML, or related; certifications in ML or AIBachelor's or master's in statistics, CS, or related; certifications in data analysis or statistics
Work EnvironmentDeveloping optimized ML models, deploying quantized models for efficiencyAnalyzing data, building predictive models, interpreting results
Industry UsageTech companies, AI hardware firms, embedded systemsFinance, healthcare, marketing, research institutions

Machine Learning Engineer Quantization focuses on optimizing ML models for deployment efficiency, often working closely with hardware and software teams. Data Scientists analyze data and build models for insights. While both roles require ML knowledge, quantization engineers specialize in model compression techniques, whereas data scientists focus on data analysis and interpretation.

What cities in Utah are hiring for Machine Learning Engineer Quantization jobs? Cities in Utah with the most Machine Learning Engineer Quantization job openings:
Infographic showing various Machine Learning Engineer Quantization job openings in Utah as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 22% Part Time, 1% Temporary, and 2% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution.

Senior ML Engineer

Waystar

Lehi, UT โ€ข On-site

$98K - $134K/yr

Full-time

Medical, Retirement, PTO

Re-posted 10 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 KLASยฎ or Category Leader awards since 2010 and earned multiple #1 rankings from Black Bookโ„ข 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.