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Executive Full Stack Machine Learning Engineer Jobs in Independence, MO

Academy Bank

Full Stack Developer

Kansas City, MO · On-site

As a Full Stack Developer, you will collaborate closely with the newly formed teams to ensure ... Azure Developer, etc.) - are advantageous and show a commitment to ongoing learning. * Experience ...

Academy Bank

Full Stack Developer

Kansas City, MO

As a Full Stack Developer, you will collaborate closely with the newly formed teams to ensure ... Azure Developer, etc.) - are advantageous and show a commitment to ongoing learning. * Experience ...

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All JobsFull Stack Machine Learning Engineer JobsExecutive Full Stack Machine Learning Engineer JobsExecutive Full Stack Machine Learning Engineer Jobs in Independence, MO

Executive Full Stack Machine Learning Engineer information

See Independence, MO salary details

$40.6K

$122.9K

$173.7K

How much do executive full stack machine learning engineer jobs pay per year?

As of Jul 13, 2026, the average yearly pay for executive full stack machine learning engineer in Independence, MO is $122,877.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,200.00 and $144,100.00 per year, depending on experience, location, and employer.

Will AI replace full-stack dev?

As an Executive Full Stack Machine Learning Engineer, it is unlikely that AI will fully replace full-stack developers, as their roles require complex problem-solving, creativity, and understanding of business needs that AI cannot replicate. AI tools can automate certain coding tasks and improve efficiency, but human oversight and expertise remain essential for designing, integrating, and maintaining full-stack applications. The evolving landscape emphasizes collaboration between AI and developers rather than replacement.

What engineer makes $500,000 a year?

An executive full stack machine learning engineer can earn $500,000 or more annually, especially with extensive experience, advanced skills in AI and software development, and working at large tech companies or startups with competitive compensation packages. High salaries often include base pay, bonuses, and stock options, reflecting seniority and expertise in the field.

Will MLE be replaced by AI?

An Executive Full Stack Machine Learning Engineer designs and implements AI systems, but AI is a tool that complements rather than replaces such roles. While automation and AI advancements can handle certain tasks, skilled engineers are needed for developing, maintaining, and improving complex machine learning solutions. Continuous learning and expertise in programming, data analysis, and model deployment remain essential in this field.

What is the salary of full-stack machine learning engineer?

The salary of a full-stack machine learning engineer typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Senior roles or those requiring specialized skills in deep learning or cloud platforms may offer higher compensation.

What is the difference between Executive Full Stack Machine Learning Engineer vs Data Scientist?

AspectExecutive Full Stack Machine Learning EngineerData Scientist
CredentialsBachelor's/Master's in CS, Engineering, or related; often requires experience in ML and full stack developmentBachelor's/Master's in Data Science, Statistics, or related; strong analytical and statistical skills
Work EnvironmentDevelops end-to-end ML solutions, integrates backend and frontend, collaborates with engineering teamsAnalyzes data, builds models, visualizes insights, often in research or analytics teams
Industry UsageUsed in tech companies, startups, and enterprises deploying ML productsCommon in research institutions, analytics firms, and data-driven organizations

The Executive Full Stack Machine Learning Engineer focuses on building and deploying complete ML solutions, combining software engineering and data science skills. In contrast, Data Scientists primarily analyze data and develop models without necessarily handling full stack development. Both roles require strong technical credentials but differ in scope and daily tasks.

What are popular job titles related to Executive Full Stack Machine Learning Engineer jobs in Independence, MO? For Executive Full Stack Machine Learning Engineer jobs in Independence, MO, the most frequently searched job titles are:
What cities near Independence, MO are hiring for Executive Full Stack Machine Learning Engineer jobs? Cities near Independence, MO with the most Executive Full Stack Machine Learning Engineer job openings:
Executive Full Stack Machine Learning Engineer jobs near you
Infographic showing various Executive Full Stack Machine Learning Engineer job openings in Independence, MO as of July 2026, with employment types broken down into 91% Full Time, 6% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $122,877 per year, or $59.1 per hour.
Machine Learning Engineer Principal

Machine Learning Engineer Principal

The University of Kansas Health System

Mission, KS • On-site

Full-time

Re-posted 8 days ago

University Of Kansas Health System rating

7.5

Company rating: 7.5 out of 10

Based on 174 frontline employees who took The Breakroom Quiz

231st of 882 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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