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Machine Learning Engineer Quantization Jobs in Salt Lake City, UT

Autonomous Solutions

AI Infrastructure Engineer IV

Lehi, UT · 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 ...

Autonomous Solutions

AI Infrastructure Engineer IV

Lehi, UT · 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 ...

Autonomous Solutions

AI Infrastructure Engineer IV

Lehi, UT · 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 compute ...

Smule

Director of Engineering

Salt Lake City, UT · On-site

Drive Smules AI-first engineering practices by embedding AI-assisted development, automation, machine learning/deep learning systems, and modern developer productivity tools into daily engineering ...

Smule

Director of Engineering

Salt Lake City, UT · On-site

Drive Smule's AI-first engineering practices by embedding AI-assisted development, automation, machine learning/deep learning systems, and modern developer productivity tools into daily engineering ...

Waystar

Sr. Data Scientist

Lehi, UT · On-site

Responsibilities : • Works closely with Application Engineering, Product Management, and Operational teams in designing, experimenting-with, and implementing machine learning and analytical systems ...

CaseWorthy, LLC

Software Engineer I

Salt Lake City, UT · On-site

$85K - $110K/yr

We're looking for early-career engineers to help us build that platform, full-stack, on a modern cloud-native stack -- with a growing data and machine-learning platform behind it, and AI features ...

iNovex Information Systems

Data Scientist 2

Ogden, UT · On-site

Job Brief Data Science, Machine Learning, Programming Are you VIGILANT about your career? RealmOne definitely is! RealmOne was built on the principle that people matter first and foremost. We believe ...

Patientco

Data Scientist

Lehi, UT · On-site

Worksclosely withApplication Engineering,ProductManagement, and Operationalteams in designing, experimenting-with,and implementing machine learning and analytical systems applied to design ...

Crew Career Center

Data Scientist

Lehi, UT

Worksclosely withApplication Engineering,ProductManagement, and Operationalteams in designing, experimenting-with,and implementing machine learning and analytical systems applied to design ...

Waystar, Inc

Data Scientist

Lehi, UT · On-site

$90 - $120/hr

Works closely with Application Engineering, Product Management, and Operational teams in designing, experimenting‑with, and implementing machine learning and analytical systems applied to design ...

Waystar

Data Scientist

Lehi, UT · On-site

Works closely with Application Engineering, Product Management, and Operational teams in designing, experimenting-with, and implementing machine learning and analytical systems applied to design ...

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Showing results 41-60

All JobsMachine Learning Engineer Quantization JobsMachine Learning Engineer Quantization Jobs in Salt Lake City, UT

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:
Machine Learning Engineer Quantization jobs near you
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.

Internship - Applied Research Scientist

Smule

Salt Lake City, UT • Remote

Other

Re-posted 9 days ago

Job description

Salary:

Smule has been on a mission to bring the world together through music since 2008. Music is much more than listening it's about creating, sharing, discovering, participating, and connecting with people. With dozens of millions of monthly active users creating over 20 million songs every day, Smule is connecting people all over the world through the joy of making music and transforming the music landscape from one of passive listening to collaborative creative expression and active engagement.


About the Role:

We are seeking a Research Scientist for Smule's Applied Research team who thrives at the intersection of cutting-edge ML research and real-world product impact. You will take ideas from the research frontier, or originate your own, and develop them into practical solutions that improve Smule's products, pipelines, and user experience for a community of millions. The ideal candidate combines research depth with strong engineering instincts, a bias toward measurable outcomes, and genuine curiosity about how people make music.


We strongly encourage candidates with non-traditional ML backgrounds to apply. If your path into applied machine learning came through audio engineering, music production, signal processing, data science, or another field, we want to hear from you.


What You'll Be Doing:

  • Develop and adapt state-of-the-art ML techniques to solve concrete product challenges in areas such as audio processing, content understanding, recommendation, and generative music, delivering measurable improvements in quality, latency, or user experience.
  • Design and run rigorous offline and online experiments (A/B tests, ablation studies) to validate model improvements before production deployment.
  • Collaborate closely with product managers, designers, and engineers to translate user needs into well-scoped research problems.
  • Build prototype models and proof-of-concept systems that demonstrate feasibility and inform production architecture decisions.
  • Publish applied research findings at relevant venues and contribute to internal knowledge-sharing through tech talks and documentation.
  • Monitor deployed models for drift, fairness, and performance, implementing continuous improvement loops.


What We're Looking For:

  • Degree (B.S., M.S., or Ph.D.) in Computer Science, Software Engineering, Electrical Engineering, or a related technical discipline, or currently pursuing one.
  • Demonstrated ability to take research ideas from paper to production, with experience shipping ML-powered features or systems.
  • Strong skills in experiment design, statistical analysis, and iterative model development.
  • Proficiency in Python, PyTorch or TensorFlow, and standard ML infrastructure (data pipelines, model serving, monitoring).
  • Effective communicator who can translate between research concepts and product requirements.
  • Track record of identifying high-impact problems and delivering solutions with measurable outcomes.


Bonus Points For:

  • Experience with audio, speech, music, or multimedia ML applications.
  • Familiarity with on-device or edge deployment constraints (model compression, quantization, latency optimization).
  • Published work at conferences or journals, such as KDD, RecSys, EMNLP, Interspeech, ISMIR, or similar.


Smule is an Equal Opportunity Employer and considers all qualified applicants without regard to race, color, religion, sex, gender identity or expression, sexual orientation, national origin, ancestry, age, disability, medical condition, genetic information, marital status, military or veteran status, or any other protected characteristic under federal, state, or local law.


We are committed to creating an inclusive environment for all employees and applicants. If you require a reasonable accommodation during the application or interview process, please let us know.