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Freelance Machine Learning Data Annotation Jobs in Kansas

Knowmadics

Senior Machine Learning Engineer

Wichita, KS · On-site

$93.50K - $128.40K/yr

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 ...

Varsity Tutors

Data Science Tutor

Overland Park, KS · Remote

$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 ...

Varsity Tutors

Data Science Tutor

Wichita, KS · Remote

$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 ...

Alignerr

Medical Science Liaison (MSL)

Kansas City, KS · Remote

Experience with data annotation, content evaluation, or AI quality review workflows * Familiarity ... Freelance perks: autonomy, variety, and global collaboration * Contribute meaningfully to AI ...

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Freelance Machine Learning Data Annotation information

What are the key skills and qualifications needed to thrive as a Freelance Machine Learning Data Annotation specialist, and why are they important?

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 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 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.

What are popular job titles related to Freelance Machine Learning Data Annotation jobs in Kansas? For Freelance Machine Learning Data Annotation jobs in Kansas, the most frequently searched job titles are:
What job categories do people searching Freelance Machine Learning Data Annotation jobs in Kansas look for? The top searched job categories for Freelance Machine Learning Data Annotation jobs in Kansas are:
What cities in Kansas are hiring for Freelance Machine Learning Data Annotation jobs? Cities in Kansas with the most Freelance Machine Learning Data Annotation job openings:
Freelance Machine Learning Data Annotation jobs near you
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Knowmadics

Wichita, KS • On-site

$93.50K - $128.40K/yr

Full-time

Posted 17 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

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