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Weekend Ai Data Annotation Jobs in Kansas (NOW HIRING)

TSMG

AI/ML Data Contributor

Wichita, KS

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

TSMG

AI/ML Data Contributor

Wichita, KS

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

TSMG

AI/ML Data Contributor

Wichita, KS · On-site

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

TSMG

AI/ML Data Contributor

Wichita, KS

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

TSMG

AI/ML Data Contributor

Wichita, KS

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

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Weekend Ai Data Annotation information

What are Weekend AI Data Annotators?

Weekend AI Data Annotators are professionals who label, categorize, and tag data—such as images, audio, or text—for use in training artificial intelligence models, specifically working on weekends. Their work ensures that machine learning algorithms receive high-quality, accurately labeled datasets for tasks like computer vision, natural language processing, or speech recognition. This role often involves using specialized annotation tools and following precise guidelines to maintain consistency and accuracy. Weekend annotators may work remotely or on-site, and their contributions are vital for improving AI system performance.

What are some common challenges faced by Weekend AI Data Annotation specialists, and how can they be managed?

Weekend AI Data Annotation specialists often encounter challenges such as maintaining high attention to detail during repetitive tasks and managing productivity over long annotation sessions. Since the work is typically remote or semi-remote, self-motivation and effective time management are crucial to meet project deadlines. It's helpful to take regular breaks, communicate proactively with team leads when questions arise, and make use of any annotation guidelines or quality assurance feedback provided. Collaborating with teammates through chat platforms or project management tools can also enhance consistency and resolve uncertainties quickly.

What are the key skills and qualifications needed to thrive as a Weekend AI Data Annotation Specialist, and why are they important?

To thrive as a Weekend AI Data Annotation Specialist, you need attention to detail, strong analytical skills, and familiarity with data labeling processes, often supported by a high school diploma or post-secondary coursework in a technical field. Proficiency with annotation platforms like Labelbox, Supervisely, or internal company tools is typically required, along with basic knowledge of data privacy protocols. Reliability, time management, and effective communication are crucial soft skills for meeting project deadlines and collaborating with remote teams. These skills and qualities ensure the accuracy and efficiency of annotated datasets, which are essential for high-performing AI systems.
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Weekend Ai Data Annotation jobs near you
AI Data Strategy Engineer / Applied Scientist, LLM Data

AI Data Strategy Engineer / Applied Scientist, LLM Data

Propio

Leawood, KS • On-site

Full-time

Posted 9 days ago

Propio rating

6.3

Company rating: 6.3 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

323rd of 451 rated business services

Job description

Description:

Propio Language Services is a provider of the highest quality interpretation, translation, and localization services. Our people take pride in every resource we offer, and our users always have access to cutting-edge technology, exceptional support, and collaborative user experiences. We are driven by our passion for innovation, growth, and bridging communication gaps in a diverse world. If you’re passionate about delivering technology-driven solutions and building lasting client relationships while contributing to client growth, Propio could be the ideal place for you.


We are building AI-powered systems that enhance multilingual communication, improve interpreter workflows, and support next-generation AI applications across text, speech, and multimodal experiences.


Propio is hiring an AI Data Strategy Engineer / Applied Scientist, LLM Data to own the data strategy, curation pipelines, annotation workflows, and evaluation datasets that power our multilingual AI systems.


This is a hands-on technical role for someone who understands how to manage the full AI data lifecycle, from acquisition, curation, annotation, and quality control to evaluation datasets and post-training data, to directly improve model performance.


The ideal candidate can build scalable data pipelines, design high-quality annotation and QA processes, identify model failure modes, and close performance gaps through targeted data acquisition, curation, and synthetic data generation.


Key Responsibilities:

  • Define the end-to-end data roadmap for multilingual and multimodal AI systems, including text, speech, translation, interpretation, low-resource languages, and agentic AI workflows.
  • Design and build dataset curation pipelines for training, post-training, and evaluation, including cleaning, deduplication, filtering, PII redaction, quality scoring, sampling, balancing, and versioning.
  • Create annotation schemas, labeling guidelines, QA rubrics, golden datasets, and reviewer workflows for multilingual, speech, translation, and agentic AI data.
  • Build evaluation datasets and benchmarks, analyze model failure modes, and translate performance gaps into targeted data improvements.
  • Support post-training data workflows such as SFT, instruction tuning, preference data, RLHF/DPO-style data, reward model data, and synthetic data generation.
  • Use modern annotation tools and AWS-based data infrastructure to scale secure, traceable, and compliant AI data workflows.


Requirements:


  • Bachelor’s degree in Computer Science, Machine Learning, Data Science, Computational Linguistics, Linguistics, Statistics, or a related field, or equivalent practical experience.
  • 4+ years of experience in AI data, ML data operations, NLP data engineering, applied ML, speech/translation data, or LLM data workflows.
  • Strong hands-on experience with Python, SQL, and dataset curation pipelines.
  • Experience with annotation workflows, QA rubrics, evaluation datasets, or human-in-the-loop data processes.
  • Familiarity with multilingual NLP, speech data, translation data, low-resource languages, conversational AI, or agentic AI datasets.
  • Working knowledge of AWS data and ML tools such as S3, Glue, SageMaker, Bedrock, Lambda, Step Functions, EKS/ECS, IAM, or KMS.
  • Strong communication skills and ability to work with ML engineers, applied scientists, product teams, linguists, data teams, and vendors.

Preferred Qualifications

  • Master’s or PhD in Computer Science, Machine Learning, NLP, Computational Linguistics, Data Science, Statistics, or a related field.
  • Experience with LLM post-training workflows such as SFT, instruction tuning, preference data, RLHF, DPO, reward modeling, or evaluation data generation.
  • Experience with synthetic data generation, active learning, weak supervision, LLM-as-judge workflows, or automated data quality scoring.
  • Experience with modern annotation and data platforms such as Labelbox, Scale AI, Prodigy, Argilla, Snorkel, Humanloop, or custom internal tooling.


What Propio employees say

Pay

Hours and flexibility

Workplace

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