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Machine Learning Engineer Quantization Jobs in Kansas

Knowmadics

Senior Machine Learning Engineer

Wichita, KS · On-site

$93K - $128K/yr

Wichita, KS; Lawton OK; or Round Rock, TX Job Purpose/Summary The Machine Learning Engineer will build and integrate machine learning solutions into our next-generation space and critical ...

Knowmadics

Senior Machine Learning Engineer

Wichita, KS · On-site

$93K - $128K/yr

As the first dedicated internal Machine Learning Engineer for this product, they willplay acriticalrole inrequirements generation, team leadership, andinfluencing the future of our products. This is ...

Bespoke Labs

Machine Learning Engineer

Topeka, KS · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Wichita, KS · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Pittsburg, KS · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

PICTOR LABS INC

$89K - $123K/yr

Prototype and productionize new inference optimization techniques, including quantization, pruning ... Strong software engineering practices including version control (Git), CI/CD, unit testing, and ...

Overstory

Role & Team As a Staff Machine Learning Engineer at Overstory, you will lead the development and scaling of our Wildfire Fuel Detection Model. This core engine powers how we understand vegetation ...

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Machine Learning Engineer Quantization information

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 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 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 Kansas?

For Machine Learning Engineer Quantization jobs in Kansas, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Quantization jobs in Kansas look for?

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Machine Learning Engineer Quantization jobs near you
Infographic showing various Machine Learning Engineer Quantization job openings in Kansas as of June 2026, with employment types broken down into 76% Full Time, 23% Part Time, and 1% Temporary. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution.

Machine Learning Engineer Principal

The University of Kansas Health System

Mission, KS • On-site

Full-time

Re-posted 14 days ago

University Of Kansas Health System rating

7.5

Company rating: 7.5 out of 10

Based on 177 frontline employees who took The Breakroom Quiz

236th of 888 rated healthcare providers

Job description

Position Title
Machine Learning Engineer Principal
Broadmoor Campus
Position Summary / Career Interest:
The Machine Learning Engineer (MLEA) Principal will lead research and development efforts to advance machine learning applications within a hospital setting. This role is also responsible for developing innovative algorithms and models to improve patient care, operational efficiency, and clinical outcomes. This role requires extensive expertise in machine learning, cloud deployment, and data engineering, with a strong emphasis on applied research and experimentation.
Responsibilities and Essential Job Functions
  • Lead and conduct advanced research in machine learning and artificial intelligence to develop novel algorithms and methodologies tailored to healthcare applications.
  • Design and implement experiments to test and validate new machine learning models and techniques, focusing on improving patient care and hospital operations.
  • Lead methodological research and implementation of methods to adjust for data set shift for healthcare applications
  • Collaborate with clinical staff, academic institutions, research labs, and industry partners to stay at the cutting edge of machine learning research and its applications in healthcare.
  • Publish research findings in top-tier conferences and journals, and present at industry events and seminars.
  • Develop and deploy state-of-the-art machine learning models using iterative development processes, based on statistical approaches and data mining techniques.
  • Identify and implement the most optimal modeling techniques based on available data types and objectives/use cases (supervised, unsupervised, semi-supervised, or reinforcement learning).
  • Implement highly efficient automated processes that produce modeling results at scale.
  • Review current offerings and future developments in artificial intelligence and machine learning and socialize these with key stakeholders to understand needs and potential use cases in the hospital.
  • Perform validation of machine learning models for accuracy and develop recommendations for enhancements based on localized data, monitor their performance post-implementation, and fine-tune for optimal results.
  • Create clear documentation of workflows, methodologies used, and assumptions built in for various levels of technical expertise.
  • Engage in the deployment and integration of predictive models and artificial intelligence into development and production environments within the hospital.
  • Advance the department's capabilities in technical and analytical areas by proactively building partnerships and collaborating with cross-functional teams.
  • Contribute to a culture of innovation, collaboration, and continuous improvement by following the latest developments in machine learning research and technology trends.
  • Able to expertly maintain existing models as well as deployment new models in both Epic and Non-Epic environments
  • Stay up to date with the latest changes from Epic to their analytics and predictive modeling applications through (e.g.) Nova Notes
  • Must be able to perform the professional, clinical and or technical competencies of the assigned unit or department.
  • These statements are intended to describe the essential functions of the job and are not intended to be an exhaustive list of all responsibilities. Skills and duties may vary dependent upon your department or unit. Other duties may be assigned as required.

Required Education and Experience
  • Bachelors Degree in Computer Science, Mathematics, Statistics, Engineering, Economics, or another computational/quantitative field (or equivalent experience)
  • 7 or more years of experience using data mining/analytical methods and associated tools such as Python, R, etc.
  • 7 or more years of experience with SQL in a relational database or an equivalent combination of education and experience
  • 5 or more years of experience with various machine learning methods: unsupervised learning, semi-supervised, supervised learning, as well as anomaly detection, natural language processing and dimensionality reduction
  • 5 or more years of experience with containerization and orchestration tools such as Docker and Kubernetes
  • 5 or more years of experience with cloud computing platforms such as Azure
  • 3 or more years of experience with Nebula, Epic's cloud computing and modeling platform

Preferred Education and Experience
  • Master's Degree in a related field OR
  • Doctorate in a related field
  • Experience working with business intelligence tools such as Power BI, Qlik, SAP Business Objects, Tableau, etc.
  • Experience with analytical documentation tools such as Jupyter Notebook
  • Experience in a relevant industry or environment

Required Licensure and Certification
  • Epic certification in 4 data model(s). If not certified, certification is required within 12 months from employment within 1 Year

Time Type:
Full time
Job Requisition ID:
R-52607
Important information for you to know as you apply:
  • The health system is an equal employment opportunity employer. Qualified applicants are considered for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, ancestry, age, disability, veteran status, genetic information, or any other legally-protected status. See also Diversity, Equity & Inclusion.
  • The health system provides reasonable accommodations to qualified individuals with disabilities. If you need to request reasonable accommodations for your disability as you navigate the recruitment process, please let our recruiters know by requesting an Accommodation Request form using this link asktalentacquisition@kumc.edu.
  • Employment with the health system is contingent upon, among other things, agreeing to the health-system-dispute-resolution-program.pdf and signing the agreement to the DRP.

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What University Of Kansas Health System employees say

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About University of Kansas Health System

Sourced by ZipRecruiter

Operating within the healthcare industry, The University of Kansas Health System is a renowned medical institution located in Kansas City, KS, United States. Established in 1905, this not-for-profit health system has evolved to offer an extensive range of products and services, which spans across a variety of specialist areas such as cancer care, neurology, cardiology, and organ transplants, among others. The core mission of The University of Kansas Health System is to enhance the health and wellness of individuals and communities by providing world-class healthcare services, quality education and conducting advanced research. They are also known for their unwavering commitment to academic medicine, which sets them apart from their peers.

Industry

Health care and social assistance

Company size

5,001 - 10,000 Employees

Headquarters location

Kansas City, KS, US

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