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Senior Machine Learning Engineer Jobs in Olathe, KS

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Sr Data & AI Scientist

Leawood, KS · On-site +1

$151K - $215K/yr

Design, build, and refresh machine learning and AI models: conduct experiments and proof-of-concept ... Partner with leadership and technical teams across the organization: collaborate with Engineering ...

AI Solutions Engineering Delivery Lead

Kansas City, MO · On-site

$100K - $131K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... As a senior technical leader, you will leverage deep technical specialization, strategic vision ...

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Senior Machine Learning Engineer information

See Olathe, KS salary details

$57.5K

$122.3K

$177.4K

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

As of Aug 24, 2026, the average yearly pay for senior machine learning engineer in Olathe, KS is $122,344.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,000.00 and $138,700.00 per year, depending on experience, location, and employer.

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

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

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What job categories do people searching Senior Machine Learning Engineer jobs in Olathe, KS look for?

The top searched job categories for Senior Machine Learning Engineer jobs in Olathe, KS are:

What cities near Olathe, KS are hiring for Senior Machine Learning Engineer jobs?

Cities near Olathe, KS with the most Senior Machine Learning Engineer job openings:

Infographic showing various Senior Machine Learning Engineer job openings in Olathe, KS as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $122,344 per year, or $58.8 per hour.

Machine Learning Engineer Principal

The University of Kansas Health System

Mission, KS • On-site

Full-time

Re-posted 19 days ago


University Of Kansas Health System rating

7.4

Company rating: 7.4 out of 10

Based on 178 frontline employees who took The Breakroom Quiz

267th of 893 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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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