1

Freelance Machine Learning Data Annotation Jobs in Lenexa, KS

Machine Learning Engineer

Mission, KS · On-site

$100 - $125/hr

As a Machine Learning Engineer, you'll build ML/AI tools that power FactualIQ's Decision Engine for ... You'll own the complete development lifecycle, from synthetic data generation and model development ...

Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment orchestration * Run and scale training experiments on cloud or HPC ...

Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment orchestration * Run and scale training experiments on cloud or HPC ...

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Data Science Tutor

Kansas City, MO · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

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 research, prepare data, and develop the underlying data models and databases needed to support new ...

Showing results 21-40

Freelance Machine Learning Data Annotation information

See Lenexa, KS salary details

$12

$20

$32

How much do freelance machine learning data annotation jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for freelance machine learning data annotation in Lenexa, KS is $20.53, according to ZipRecruiter salary data. Most workers in this role earn between $16.25 and $23.46 per hour, depending on experience, location, and employer.

What is freelance machine learning data annotation?

Freelance machine learning data annotation involves labeling or tagging data—such as images, text, audio, or video—to help train machine learning models. As a freelancer, you work independently or through platforms, completing specific annotation tasks assigned by companies or researchers. This work is essential because high-quality labeled data is required for AI systems to learn and make accurate predictions. Annotators may categorize images, transcribe speech, or highlight relevant information in documents. The flexibility of freelancing allows you to choose projects and work remotely.

What are the key skills and qualifications needed to thrive as a freelance machine learning data annotation specialist?

To thrive as a Freelance Machine Learning Data Annotation specialist, you need attention to detail, basic knowledge of data labeling concepts, and familiarity with machine learning data types. Experience with annotation tools (such as Labelbox, RectLabel, or CVAT) and understanding of data privacy protocols are commonly required. Strong communication, time management, and the ability to follow complex guidelines are essential soft skills for delivering accurate results. These skills ensure high-quality, consistent data annotation, which is critical for effective machine learning model training and performance.

What are some common challenges faced by freelance machine learning data annotators, and how can they be managed?

Freelance machine learning data annotators often encounter challenges such as maintaining data accuracy, handling repetitive tasks, and understanding complex annotation guidelines. Staying organized and regularly reviewing project instructions can help ensure consistency and quality in annotations. Additionally, communicating proactively with project managers and utilizing annotation tools efficiently can help manage workload and clarify uncertainties. Building expertise in different data types (text, image, audio) also allows annotators to diversify their projects and reduce monotony.

What is the difference between Freelance Machine Learning Data Annotation vs Data Labeler?

AspectFreelance Machine Learning Data AnnotationData Labeler
CredentialsBasic understanding of annotation tools, sometimes with specialized domain knowledgeTypically no formal credentials required
Work EnvironmentRemote, flexible, project-basedOften remote or in-house, depending on employer
Industry UsageUsed in AI/ML development for training datasetsUsed in data preparation for various industries, including AI
Search/Comparison IntentFocuses on freelance opportunities, project scope, and toolsMore general, often employed by companies for data labeling tasks

Freelance Machine Learning Data Annotation involves independently completing annotation tasks for AI models, often with specialized tools and domain knowledge. Data Labelers typically perform similar tasks but may work as employees or contractors within a company. The main difference lies in the freelance nature and project-based work of data annotation roles.

Can I work for freelance machine learning data annotation with no experience?

Freelance machine learning data annotation jobs often do not require prior experience, as many tasks involve simple labeling or categorization that can be learned quickly. Basic computer skills, attention to detail, and familiarity with annotation tools are helpful, and training is usually provided. However, building a portfolio or gaining some familiarity with data annotation platforms can improve job prospects.

What cities near Lenexa, KS are hiring for Freelance Machine Learning Data Annotation jobs?

Cities near Lenexa, KS with the most Freelance Machine Learning Data Annotation job openings:

Infographic showing various Freelance Machine Learning Data Annotation job openings in Lenexa, KS as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, 1% Temporary, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $42,695 per year, or $20.5 per hour.

Research Engineer - Machine Learning & Robotics

Lenexa, KS • On-site

Jumio
Software Development • 1 - 5K employees

Full-time

Re-posted 15 days ago


Job description

Role Purpose
Jumio is looking for a Research Engineer with a foundation in machine learning, robotics, and data infrastructure to help build and scale the systems used for data collection, model development, and product improvement.
This role sits at the intersection of robotics, computer vision, and applied machine learning. You will work hands-on with robotic systems, ROS/ROS2-based modules, mobile data collection workflows, and ML pipelines that support training, evaluation, and production model performance. This is a strong opportunity for a new graduate or early-career engineer who wants to build practical systems that directly improve real-world AI products.
Role Value
High-quality data and reliable model evaluation infrastructure are critical to improving Jumio's machine learning and computer vision capabilities. This role helps ensure that data collected from robotic systems and mobile applications is usable, scalable, and connected to the broader model development lifecycle.
The Research Engineer will support both the robotics/data collection environment and the ML development workflow, helping the team move faster, improve model quality, and better understand model performance in production.
Example Responsibilities
  • Build and integrate ROS/ROS2-based modules to support robotic navigation, manipulation, and data collection workflows.
  • Replicate and integrate mobile and web UI environments into robotic testing and data collection systems.
  • Build, maintain, and improve training and test datasets collected through robotic manipulators and in-house iOS and Android applications.
  • Mine, query, and analyze data from internal databases to create features, identify trends, and generate insights that improve product and model development.
  • Develop tools and processes to monitor data quality, model performance, and model accuracy in production environments.
  • Implement end-to-end machine learning workflows, including data preparation, model training, testing, evaluation, and deployment support.
  • Write clean, modular, well-documented C++ and Python code that can be maintained and extended by other engineers.
  • Collaborate cross-functionally with machine learning, engineering, product, and research teams to improve data collection, model development, and system performance.
Required Experience
  • Bachelor's or Master's degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field.
  • 1-2 years of relevant industry, internship, or research experience in machine learning, robotics, computer vision, or related technical areas.
  • Hands-on experience with ROS and/or ROS2, including building or integrating modules for robot navigation, manipulation, simulation, or data collection.
  • Strong foundation in machine learning fundamentals, with experience implementing models in Python using frameworks such as PyTorch, TensorFlow, scikit-learn, or similar.
  • Experience working with databases, writing queries, and building or maintaining data pipelines for training, testing, or evaluation.
  • Strong programming skills in Python and C++, with an emphasis on clean, reliable, well-documented code.
  • Ability to work hands-on with physical hardware, debug system behavior, and translate research or prototype work into scalable engineering solutions.
Nice to Have
  • Experience with robotic manipulators, mobile robot platforms, or lab-based robotic systems.
  • Familiarity with iOS and/or Android development, especially for hardware-integrated data collection applications.
  • Experience with data collection pipelines for computer vision, biometric systems, identity verification, or similar applied AI domains.
  • Exposure to production ML observability, model monitoring, drift detection, or data quality monitoring tools.
  • Familiarity with cloud platforms such as AWS, including S3, EC2, SageMaker, or similar tools for storage, compute, and model deployment.
  • Experience working in cross-functional environments with machine learning engineers, software engineers, researchers, and product teams.

Jumio Values:
IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation
Equal Opportunities:
Jumio is a collaboration of people with different ideas, strengths, interests and cultures. We welcome applications and colleagues from all backgrounds and of all statuses.
About Jumio:
Jumio is a B2B technology company dedicated to eradicating online identity fraud, money laundering and other financial crimes to help make the internet safer. We leverage AI, biometrics, machine learning, liveness detection and automation to create solutions that are trusted by leading brands worldwide and respected by industry thought leaders.
Jumio is the leading provider of online identity verification, eKYC and AML solutions. With a global footprint, we're expanding the team to meet strong client demand across a range of industries including Financial Services, Travel, Sharing Economy, Fintech, Gaming, and others.
Applicant Data Privacy
We will only use your personal information in connection with Jumio's application, recruitment, and hiring processes, as described in Jumio's Applicant Privacy Notice. If you have any questions or comments, please send an email to privacy@jumio.com.