1

Machine Learning Engineer Quantization Jobs in Salt Lake City, UT

Senior ML Engineer

Lehi, UT · 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 ...

Senior ML Engineer

Lehi, UT

$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 ...

Senior ML Engineer

Lehi, UT · 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 · 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 · 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 · 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 ...

Senior AI/ML Engineer

Draper, UT · 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 · 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 ...

Showing results 21-40

Machine Learning Engineer Quantization information

See Salt Lake City, UT salary details

$30.5K

$124.6K

$187.3K

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

As of Aug 11, 2026, the average yearly pay for machine learning engineer quantization in Salt Lake City, UT is $124,611.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,200.00 and $150,000.00 per year, depending on experience, location, and employer.

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 are popular job titles related to Machine Learning Engineer Quantization jobs in Salt Lake City, UT? For Machine Learning Engineer Quantization jobs in Salt Lake City, UT, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Salt Lake City, UT look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Salt Lake City, UT are:
Infographic showing various Machine Learning Engineer Quantization job openings in Salt Lake City, UT 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, with an average salary of $124,611 per year, or $59.9 per hour.

Artificial Intelligence (AI) / Machine Learning (ML) Engineers

University of Utah

Salt Lake City, UT • On-site

$90K - $135K/yr

Full-time

Retirement

Posted 19 days ago


University Of Utah rating

7.2

Company rating: 7.2 out of 10

Based on 159 frontline employees who took The Breakroom Quiz

382nd of 617 rated colleges and universities


Job description

Announcement
Details
Open Date
07/23/2026
Requisition Number
PRN45731B
Job Title
Artificial Intelligence (AI) / Machine Learning (ML) Engineers
Working Title
AI Engineer
Career Progression Track
P00
Track Level
P4 - Advanced, P3 - Career
FLSA Code
Computer Employee
Patient Sensitive Job Code?
No
Standard Hours per Week
40
Full Time or Part Time?
Full Time
Shift
Day
Work Schedule Summary
Work Schedule
Full-time, 40 hours per week. Monday through Friday from 8:00 am to 5:00 pm.
Work Location & Residency
This position offers a flexible, mostly remote work schedule for candidates who reside along the Wasatch Front. While most duties can be performed remotely, the employee must be available to attend essential meetings and events on campus as needed.
Work Profile
Hybrid Work
A hybrid telework schedule is available for this position, dependent on operational needs and management approval. The arrangement will be established in partnership with the manager and is subject to ongoing departmental needs.
Travel:
This position may require occasional travel.
VP Area
U of U Health - Academics
Department
02228 - Data Coordinating Center
Location
Campus
City
Salt Lake City, UT
Type of Recruitment
External Posting
Pay Rate Range
$90,188 to $135,601
Close Date
10/23/2026
Priority Review Date (Note - Posting may close at any time)
Job Summary
Artificial Intelligence (AI) / Machine Learning (ML) Engineers
The Utah Data Coordinating Center (DCC) is seeking an experienced AI Engineer to design, build, and operate secure, scalable AI-enabled research platforms. This role sits at the intersection of machine learning, cloud infrastructure, and regulated research environments, supporting national and international research programs. You will work closely with research IT leadership, data engineers, security teams, and external partners to operationalize AI workflows while maintaining strong governance, security, and compliance standards. This is a hands-on engineering role for someone who enjoys building real systems, not prototypes that live on slides. This position will report to the Sr. Supervisor, IT.
Essential Functions:
  • Design and deliver end-to-end hybrid data and AI solutions
    Collaborate with data scientists, engineers, and business stakeholders to design, build, test, deploy, and support scalable data pipelines and AI/ML models across hybrid cloud and on-premises environments. Deliver reliable, production-ready solutions aligned with organizational strategy and enterprise architecture standards.
  • Operationalize machine learning systems using modern MLOps practices
    Partner with cross-functional teams to deploy, monitor, and manage ML models through CI/CD pipelines, model versioning, experiment tracking, automated testing, and lifecycle management frameworks. Support both batch and real-time inference workloads while ensuring reliability, scalability, and maintainability.
  • Build and maintain secure, scalable infrastructure across hybrid environments
    Implement containerized and cloud-native solutions using Docker and orchestration platforms (e.g., Kubernetes) to support data and AI workloads. Apply infrastructure-as-code (IaC) and automation practices to enable reproducibility, scalability, and operational efficiency across on-premises and cloud systems.
  • Ensure secure, compliant, and governed data and AI systems
    Collaborate with security and compliance teams to implement role-based access controls, encryption, network security controls, and audit logging across environments. Align architectures with regulatory frameworks (e.g., HIPAA, NIST, FISMA) and enterprise governance standards while promoting responsible AI practices.
  • Translate business requirements into scalable technical architectures
    Engage with stakeholders to understand strategic objectives and convert them into robust data architectures, algorithms, and automation workflows. Promote shared ownership of solutions, ensuring alignment with long-term sustainability, performance expectations, and enterprise standards.
  • Monitor, optimize, and sustain production systems
    Implement monitoring, logging, and alerting frameworks to track data pipeline health, model performance, data drift, system reliability, and cost efficiency. Apply performance tuning, reliability engineering, and continuous improvement practices to maintain operational excellence.
  • Communicate technical designs and analytical insights clearly
    Document system architectures, data flows, AI workflows, and operational procedures. Present complex technical concepts and model outcomes to both technical and non-technical stakeholders in a clear and actionable manner.
  • Advance engineering excellence and innovation
    Stay current with emerging technologies in data engineering, cloud computing, and applied AI. Evaluate and adopt new tools and methodologies that improve automation, scalability, security, and organizational impact while adhering to best practices and architectural standards.

To learn more about the Utah DCC visit http://uofuhealth.org/UtahDCCThis position is not eligible for work visa sponsorship.
The University of Utah offers a comprehensive benefits package. You can learn more about the great benefits of working for the University of Utah at: benefits.utah.edu
The department may choose to hire at any of the below job levels and associated pay rates based on their business need and budget.
Responsibilities
Artificial Intelligence (AI) / Machine Learning (ML) EngineerResearch, design, develop, test, and support artificial intelligence (AI) and machine learning (ML) frameworks and models. Leverage AI/ML techniques to answer business questions, support business strategies, and deliver valuable quantitative insights to improve products. Develop sophisticated algorithms to automate processes and tasks. Collaborate with internal stakeholders to understand business and technical needs. Code and develop software that deploys ML models and algorithms into production. Communicate and present complex analytics results and concepts to leadership and internal stakeholders. Employ AI and/or ML that may include natural language processing (NLP), natural language understanding (NLU), semantic understanding, intent classification, computer vision, deep learning, and automatic speech recognition (ASR). Remain up to speed on cutting edge research for AI technology and concepts.
Artificial Intelligence (AI) / Machine Learning (ML) Engineer, IIIConsidered highly skilled and proficient in discipline. Conducts complex, important work under minimal supervision and with wide latitude for independent judgment.
Requires a bachelor's (or equivalency) + 6 years or a master's (or equivalency) + 4 years of directly related work experience.
This is a Career-Level position in the General Professional track.
Expected Pay Range: $90,188 to $123,274
Artificial Intelligence (AI) / Machine Learning (ML) Engineer, IV
Recognized as subject matter expert and advanced individual contributor professional. Requires specialized skill set. Conducts highly complex work, unsupervised and with extensive latitude for independent judgment.
Requires a bachelor's (or equivalency) + 8 years or a master's (or equivalency) + 6 years of directly related work experience.
This is an Advanced-Level position in the General Professional track.
Expected Pay Range: $99,587 to $135,601
Minimum Qualifications
EQUIVALENCY STATEMENT: 1 year of higher education can be substituted for 1 year of directly related work experience (Example: bachelor's degree = 4 years of directly related work experience).
Department may hire employee at one of the following job levels:
Artificial Intelligence (AI) / Machine Learning (ML) Engineer, III: Requires a bachelor's (or equivalency) + 6 years or a master's (or equivalency) + 4 years of directly related work experience.
Artificial Intelligence (AI) / Machine Learning (ML) Engineer, IV: Requires a bachelor's (or equivalency) + 8 years or a master's (or equivalency) + 6 years of directly related work experience.
Preferences
  • Experience with MLOps platforms or custom ML deployment pipelines
  • Familiarity with vector databases, embeddings, or RAG-based systems
  • Experience supporting clinical research, biomedical data, or sensitive datasets
  • Familiarity with compliance-driven environments (FISMA Moderate/High, HITRUST, etc.)
  • Experience working in academic or research institutions
  • Strong experience with Python and modern ML/AI tooling
  • Hands-on experience with AWS (or comparable cloud platforms)
  • Experience building and operating CI/CD pipelines
  • Proficiency with Docker and container-based workflows
  • Experience supporting data-intensive or research computing environments
  • Strong understanding of security best practices in regulated environments
  • Ability to work independently and communicate clearly with both technical and non-technical stakeholders

Applicants will be screened according to preferences.
Type
Benefited Staff
Special Instructions Summary
Additional Information
The University is a participating employer with Utah Retirement Systems ("URS"). Eligible new hires with prior URS service, may elect to enroll in URS if they make the election before they become eligible for retirement (usually the first day of work). Contact Human Resources at (801) 581-7447 for information. Individuals who previously retired and are receiving monthly retirement benefits from URS are subject to URS' post-retirement rules and restrictions. Please contact Utah Retirement Systems at (801) 366-7770 or (800) 695-4877 or University Human Resource Management at (801) 581-7447 if you have questions regarding the post-retirement rules.
This position may require the successful completion of a criminal background check and/or drug screen.
The University of Utah values candidates who have experience working in settings with students and possess a strong commitment to improving access to higher education.
Veterans' preference is extended to qualified applicants, upon request and consistent with University policy and Utah state law. Upon request, reasonable accommodations in the application process will be provided to individuals with disabilities.
Consistent with state and federal law, the University of Utah does not discriminate based upon race, ethnicity, color, religion, national origin, age, disability, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, pregnancy-related conditions, genetic information, or protected veteran's status. The University does not discriminate on the basis of sex in the education program or activity that it operates, as required by Title IX and 34 CFR part 106. The requirement not to discriminate in education programs or activities extends to admission and employment. Inquiries about the application of Title IX and its regulations may be referred to the Title IX Coordinator, to the Department of Education, Office for Civil Rights, or both.
To request a reasonable accommodation for a disability or if you or someone you know has experienced discrimination or sexual misconduct including sexual harassment, you may contact the Director/Title IX Coordinator in the Office of Equal Opportunity and Title IX (OEO). More information, including the Director/Title IX Coordinator's office address, electronic mail address, and telephone number can be located at the: University of Utah Non-Discrimination page.
Online reports may be submitted at https://oeo.utah.edu
https://publicsafety.utah.edu/safetyreport/ This report includes statistics about criminal offenses, hate crimes, arrests and referrals for disciplinary action, and Violence Against Women Act offenses. They also provide information about safety and security-related services offered by the University of Utah. A paper copy can be obtained by request at the Department of Public Safety located at 1658 East 500 South.
As per University of Utah policy 5-108: Transfer of Benefits Eligible Staff Members, a new hire to the University of Utah who is still serving a 12 month probationary period will not be hired into another University of Utah job (a transfer) until the successful completion of the probationary period.

What University Of Utah employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


University of Utah logo

About University of Utah

Sourced by ZipRecruiter

The University of Utah is the state’s flagship institution of higher education, with 18 schools and colleges, more than 100 undergraduate majors and graduate programs, and an enrollment of more than 38,000 students. It is a member of the Association of American Universities—an invitation-only, prestigious group of 71 leading research institutions. The U is advancing a new national model for higher education that delivers societal impact through education, research, health care, and community service, while making social, economic, and cultural contributions that improve lives across Utah and around the world.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Salt Lake City, UT, US

Year founded

1850