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Machine Learning Engineer Jobs in Wichita, KS (NOW HIRING)

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 ...

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 ...

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 ...

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 ...

Machine Learning Tutor

Wichita, KS · Remote

$18 - $40/hr

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

Experience applying artificial intelligence (AI), machine learning (ML), and advanced data engineering to cybersecurity use cases, including detection and cyber threat response acceleration

In this role, you will assist in improving machine learning models through tasks such as data labeling, content evaluation, and user-based testing. Responsibilities : • Perform AI/ML-related tasks ...

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Machine Learning Engineer information

See Wichita, KS salary details

$28.2K

$115.2K

$173.1K

How much do machine learning engineer jobs pay per year?

As of Aug 6, 2026, the average yearly pay for machine learning engineer in Wichita, KS is $115,202.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,800.00 and $138,700.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are popular job titles related to Machine Learning Engineer jobs in Wichita, KS? For Machine Learning Engineer jobs in Wichita, KS, the most frequently searched job titles are:
What cities near Wichita, KS are hiring for Machine Learning Engineer jobs? Cities near Wichita, KS with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Wichita, KS as of August 2026, with employment types broken down into 76% Full Time, and 24% Contract. Highlights an 74% In-person, and 26% Remote job distribution, with an average salary of $115,202 per year, or $55.4 per hour.

Senior Machine Learning Engineer

Knowmadics

Wichita, KS • On-site

$93K - $128K/yr

Full-time

Re-posted 27 days ago


Job description

Candidate should live within driving distance of the following areas: 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 infrastructure defense capabilities. They will leverage a variety of machine learning approaches to process very large streams of unstructured data in real time in scalable and secure cloud-native environments. As the first dedicated internal Machine Learning Engineer for this product, they will play a critical role in requirements generation, team leadership, and influencing the future of our products.
This is a demanding product development role, not a research position. Success on year one involves the design, training, optimization, validation and implementation of high-performance inference pipelines at scale.The role will play a key part in building and delivering initial machine learning capabilities for our MVP offering and may evolve over time to include involvement in hiring and mentorship as the team grows.
Duties and Responsibilities
  • Lead the development + implementation of real-time feature detection and anomaly detection models
  • Generate data characteristic requirements for real-time data processing pipelines
  • Prepare technical documentation, reports, and specifications
  • Collaborate with cross-functional teams including project managers, technicians, and other engineers
  • Perform testing, troubleshooting, and quality assurance on systems or products
  • Ensure compliance with safety regulations, industry standards, and company policies

Qualifications
  • 7-10 YoE as a SWE or ML engineer building applied research and/or production technologies
  • Expertise on building production training and inference pipelines in python
  • A strong familiarity and personal preference for one or more deep learning libraries (ex. pytorch)
  • A comprehensive understanding of systems programming (a strong proficiency in C would imply this)
  • An understanding of how ETL processing works and familiarity with some of the common tools (kafka, spark, etc.)
  • Experience building machine learning models for unstructured data types (text, imagery, RF, telemetry, etc.)
  • Experience with hardware acceleration (GPUs, CUDA) for training and inference workloads
  • Experience packaging and deploying trained inference models for use in production environments
  • Minimum education requirement: High school diploma
  • Eligible to obtain a U.S. Security Clearance - U.S. Citizenship required.

Bonus Qualifications
  • Experience integrating trained inference pipelines into scalable cloud-native infrastructure
  • Experience building backend services and implementing API endpoints for scalable infrastructure
  • Experience building technology for air-gapped production deployment environments
  • Knowledge and experience with OCI technologies (docker, kubernetes, helm etc.)
  • B.S. or M.S. in an area relevant to this role

Working conditions
  • Employees may be called upon to participate in in-person meetings, training, or company functions at Knowmadics offices or other designated locations. Travel in support of business operations may also be required, and employees are expected to comply with these obligations as part of their position.
  • Candidate should live within driving distance of the following areas: Waldorf, Md; Wichita, KS; Lawton OK; or Round Rock, TX
  • Estimated Travel: 0-10%

Physical requirements
May include sitting or standing for extended periods, working with computers and technical equipment, and occasionally lifting or moving materials or tools.
Direct reports
None