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Freelance Machine Learning Data Annotation Jobs in Wichita, KS

Technical Product Manager

Newton, KS

$147K - $170K/yr

Drive the integration or application of advanced technologies, machine learning and artificial ... Oversee product for our data governance programs, collaborating with teams to ensure that data is ...

Ability to explain statistical modeling techniques, machine learning basics, and business intelligence dashboard design while preparing students for analytics roles and data-driven management ...

Python Tutor

Wichita, KS · Remote

$18 - $40/hr

... data with Pandas, creating visualizations, implementing class hierarchies, and automating tasks with scripts. Emphasizes readable, maintainable code and connects Python to machine learning, web ...

... machine learning (ML), generative AI, and agentic AI workloads on AWS, including Amazon Bedrock and Amazon SageMaker, as well as mitigation of risks such as prompt injection, model exfiltration, data ...

Linear Algebra Tutor

Wichita, KS · Remote

$18 - $40/hr

... data science, engineering, and advanced mathematics. * Conceptual Teaching & Problem-Solving ... machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive Instruction:

Showing results 41-60

Freelance Machine Learning Data Annotation information

See Wichita, KS salary details

$11

$19

$31

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

As of Sep 3, 2026, the average hourly pay for freelance machine learning data annotation in Wichita, KS is $19.56, according to ZipRecruiter salary data. Most workers in this role earn between $15.48 and $22.36 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.

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For Freelance Machine Learning Data Annotation jobs in Wichita, KS, the most frequently searched job titles are:

What job categories do people searching Freelance Machine Learning Data Annotation jobs in Wichita, KS look for?

The top searched job categories for Freelance Machine Learning Data Annotation jobs in Wichita, KS are:

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

Infographic showing various Freelance Machine Learning Data Annotation job openings in Wichita, KS as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 19% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $40,689 per year, or $19.6 per hour.

Applied Research Intern, Proactive Intelligence & Customer World Models (PhD / Graduate Co-op)

Block

Wichita, KS • Remote

Full-time

Posted 5 days ago


Block rating

7.9

Company rating: 7.9 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

9th of 21 rated payment service providers


Job description

Team: Apollo - Block Applied R&D Location: Remote (US / Canada) Duration: Fall/Winter 2026 co-op - 8 months, flexible start September 2026 Level: Graduate student (MS or PhD, returning to your program after the co-op)

About Apollo

Apollo leads Block's efforts to build the Customer World Model (CWM): a continuously evolving representation of each customer's goals, context, history, constraints, and likely future needs.

The CWM powers proactive intelligence across Block's ecosystem. Instead of customers navigating products in search of features, intelligence observes their world, understands what matters, anticipates what comes next, and initiates actions on their behalf.

We believe the next generation of AI products will not be defined by chat interfaces or isolated agents. They will be defined by rich world models that enable systems to reason over a customer's evolving state, make better decisions, and learn continuously from outcomes. Apollo designs, prototypes, and guides the development of this intelligence layer.

About the role

We're hiring a small cohort of graduate research interns to help build the foundations of proactive intelligence.

This is not a traditional internship. You'll own a research problem end-to-end: framing the question, developing methods, running experiments, publishing findings, and, when successful, shipping your work into production systems used by millions of customers and sellers.

You'll work at the intersection of representation learning, foundation models, reinforcement learning, causal reasoning, agentic systems, and product intelligence. The goal is not simply to build smarter models, but to build systems that develop a deeper understanding of customers and use that understanding to make better decisions over time.

Past interns have shipped production systems within months and published their work in the same year.

What you'll work on

Depending on your interests and Apollo's roadmap, you'll focus on one or more of the following areas:

Customer World Models

Building rich representations of customers from event streams, financial activity, operational signals, and behavioral data.

Examples include:

  • Representation learning over long-horizon customer histories
  • Event-based foundation models
  • Multi-modal customer representations spanning structured, sequential, and graph data
  • Memory architectures for long-term customer understanding

Proactive Intelligence

Developing systems that can anticipate customer needs and initiate helpful actions before being asked.

Examples include:

  • Opportunity detection and next-best-action systems
  • Long-horizon planning and decision-making
  • Preference and goal inference
  • Learning when intervention creates value versus friction

Agentic Decision Systems

Building agents that reason over customer world models and take actions in real environments.

Examples include:

  • Tool use and planning
  • Multi-step reasoning over customer state
  • Autonomous workflow execution
  • Recovery and adaptation under uncertainty

Learning from Feedback Loops

Developing methods that allow intelligence to improve continuously from real-world outcomes.

Examples include:

  • Reinforcement learning from customer and product feedback
  • Reward modeling and preference learning
  • Counterfactual evaluation
  • Credit assignment over long decision horizons

Evaluation and Measurement

Building evaluation frameworks that predict real-world performance, trust, and customer value.

Examples include:

  • Simulated customer environments
  • Longitudinal evaluation
  • Decision quality metrics
  • Safety and reliability benchmarks

What we're looking for

We're looking for researchers interested in building systems that understand people, learn from experience, and improve over time.

Required

  • Currently enrolled in an MS or PhD program in Computer Science, Machine Learning, Statistics, Mathematics, Operations Research, or a related field, and returning to that program after the co-op.
  • Strong foundations in modern machine learning, including deep learning, optimization, representation learning, and foundation models.
  • Experience conducting independent research and translating ideas into working systems.
  • Fluency in Python and experience with PyTorch, JAX, or similar frameworks.
  • Evidence of research excellence through publications, open-source contributions, technical leadership, or equivalent work.

Nice to have

  • Experience with large language models and agentic systems.
  • Experience with reinforcement learning, reward modeling, or sequential decision-making.
  • Experience with representation learning for structured, temporal, or graph data.
  • Familiarity with large-scale training and production ML systems.
  • Interest in building AI systems that directly affect customer outcomes.

What you'll get

  • Direct mentorship from researchers working on the future of proactive intelligence at Block.
  • Access to large-scale datasets, modern infrastructure, frontier models, and substantial compute resources.
  • Opportunities to publish and contribute to open-source projects.
  • A chance to shape foundational technology that could power the next generation of Block products.
  • Exposure to both scientific research and product deployment, with a clear path from idea to impact.

Application Guidelines

Candidates may submit up to 9 active applications within a 60-day period. Reapplications to the same role are accepted 90 days after a previous application has been reviewed.

Use of AI in Our Hiring Process

We may use automated AI tools to evaluate job applications for efficiency and consistency. These tools comply with local regulations, including bias audits, and we handle all personal data in accordance with state and local privacy laws.

Contact us here with hiring practice or data usage questions.

Every benefit we offer is designed with one goal: empowering you to do the best work of your career while building the life you want. Remote work, medical insurance, flexible time off, retirement savings plans, and modern family planning are just some of our offering. Check out our other benefits at Block.

Block, Inc. (NYSE: XYZ) builds technology to increase access to the global economy. Each of our brands unlocks different aspects of the economy for more people. Square makes commerce and financial services accessible to sellers. Cash App is the easy way to spend, send, and store money. Afterpay is transforming the way customers manage their spending over time. TIDAL is a music platform that empowers artists to thrive as entrepreneurs. Bitkey is a simple self-custody wallet built for bitcoin. Proto is a suite of bitcoin mining products and services. Together, we're helping build a financial system that is open to everyone.


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