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Remote Data Labeling Jobs in Missouri (NOW HIRING)

Jobgether

$11.50 - $15.50/hr

You will help learners understand how data labeling influences machine learning systems, generative ... This is a part-time contract position with a remote setup and scheduled sessions aligned with the ...

Jobgether

Review and evaluate graphic design samples using a dedicated data-labeling platform and ... Previous remote work experience and the ability to manage self-directed tasks are advantageous.

GRVTY

Imagery Scientist (EO) - Senior

Saint Louis, MO · On-site +1

$160K - $190K/yr

... data standards or to be transformed into a usable state for labeling and model testing purposes ... Remote sensing phenomenology * Image formation processes * Exploitation products and methodologies

GRVTY

Imagery Scientist (EO)- Expert

Saint Louis, MO · On-site +1

$180K - $210K/yr

Data formats * APIs and ETL processes * Existing operational pipelines * Develop strategies to ... Labeling * Model testing * Advanced exploitation workflows * Investigate gaps in emerging EO sensor ...

All JobsData Labeling JobsRemote Data Labeling JobsRemote Data Labeling Jobs in Missouri

Remote Data Labeling information

What is remote data labeling?

A Remote Data Labeling job involves annotating or categorizing data, such as images, text, audio, or video, to train machine learning models. Workers review and tag content based on specific guidelines provided by companies. This job is typically done online from home and requires attention to detail, consistency, and sometimes specialized domain knowledge. It plays a crucial role in improving artificial intelligence systems by providing high-quality labeled data.

What skills and qualifications are needed for remote data labeling?

To thrive as a Remote Data Labeling specialist, you need strong attention to detail, basic data analysis skills, and the ability to accurately tag and categorize diverse data types, often with a high school diploma or equivalent. Familiarity with data labeling platforms, annotation tools (such as Labelbox or Amazon SageMaker Ground Truth), and, occasionally, basic knowledge of data privacy standards is helpful. Time management, self-discipline, and effective remote communication are valuable soft skills in this position. These skills ensure that labeled data is accurate and reliable, supporting the success of machine learning and AI projects.

What are common challenges faced by remote data labelers, and how can they be managed?

Remote data labelers often face challenges such as maintaining focus during repetitive tasks, managing volume-based workloads, and interpreting ambiguous data with consistency. To manage these, it's important to set up a distraction-free workspace, take regular breaks to avoid fatigue, and seek clarification from supervisors or project guidelines when uncertainties arise. Most companies provide onboarding and ongoing support to help new labelers understand annotation standards and best practices. Collaborating with remote team members via chat or project management platforms also helps maintain quality and stay connected. By being proactive and utilizing available resources, remote data labelers can maintain high accuracy and productivity.

What are the most commonly searched types of Data Labeling jobs in Missouri?

The most popular types of Data Labeling jobs in Missouri are:

What are popular job titles related to Remote Data Labeling jobs in Missouri?

For Remote Data Labeling jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Remote Data Labeling jobs in Missouri look for?

The top searched job categories for Remote Data Labeling jobs in Missouri are:

What cities in Missouri are hiring for Remote Data Labeling jobs?

Cities in Missouri with the most Remote Data Labeling job openings:

Remote Data Labeling jobs near you
Infographic showing various Remote Data Labeling job openings in Missouri as of August 2026, with employment types broken down into 53% Full Time, 21% Part Time, and 26% Contract. Highlights an 100% Remote job distribution.

Lead Instructor: Machine Learning Data Associate

Jobgether

Remote

$11.50 - $15.50/hr

Full-time

Posted 5 days ago

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Instructor: Machine Learning Data Associate based in Netherlands.

This is an opportunity to lead engaging, high-impact virtual learning experiences for diverse audiences developing skills in machine learning and AI data workflows. You will deliver live technical instruction in German while collaborating professionally in English with program and operations teams. The role combines technical expertise, instructional leadership, and the ability to make complex AI concepts practical and accessible. You will help learners understand how data labeling influences machine learning systems, generative AI, multimodal models, and applied AI workflows. Sessions may range from smaller groups to audiences of thousands of learners in a highly interactive online environment. You will also contribute to curriculum refinement and continuous course improvement. This is a part-time contract position with a remote setup and scheduled sessions aligned with the EST/CEST time zones.

Accountabilities
  • Lead and facilitate live virtual classes for diverse learner groups, potentially ranging from 100 to more than 8,000 participants, while maintaining strong engagement and an effective learning environment.
  • Deliver technical instruction in German on machine learning data workflows, generative AI, foundation models, prompt engineering, RAG, multimodal AI, responsible AI, and related concepts.
  • Explain how data collection, annotation, labeling decisions, model training, evaluation, and deployment are connected, helping learners understand the downstream impact of their work.
  • Manage virtual classroom dynamics, including Q&A, chat activity, pacing, learner engagement, and timely delivery of planned content.
  • Adapt instructional approaches, explanations, and lesson pacing to accommodate learners with different backgrounds and levels of technical understanding.
  • Prepare thoroughly for each lecture and ensure that technical content is delivered accurately, clearly, and in an accessible manner.
  • Collaborate with program and operations teams in English to support smooth delivery, communicate updates, escalate issues, and maintain alignment on schedules and learner needs.
  • Contribute to curriculum design and continuous improvement, including suggesting edits, refining lessons, and supporting the development of hands-on learning activities.
  • Provide constructive feedback before and after sessions to strengthen course quality and learner outcomes.
  • Maintain a professional, respectful, responsive, and empathetic presence when interacting with learners, colleagues, contractors, and guest speakers.
Requirements:
  • Fluency in German sufficient to deliver all instruction and learner support professionally, combined with strong English proficiency for written communication, meetings, alignment, and issue escalation.
  • Strong practical understanding of the machine learning lifecycle, including data collection, model training, evaluation, and deployment, with the ability to explain how labeling decisions affect model behavior and downstream outputs.
  • Solid knowledge of generative AI and foundation models, including concepts such as pre-training, fine-tuning, reinforcement learning from human feedback (RLHF), and human feedback for model alignment.
  • Hands-on experience with prompt engineering, including zero-shot, one-shot, and few-shot prompting, and the ability to teach learners how to interpret requirements, identify task constraints, and evaluate output quality.
  • Working knowledge of Retrieval-Augmented Generation (RAG) and production AI workflows, including the ability to explain how to assess outputs for relevance, faithfulness, and groundedness.
  • Understanding of multimodal and cross-modal AI, including how models process and generate text, images, audio, and video, and how these capabilities influence annotation and evaluation tasks.
  • Knowledge of responsible AI, privacy, confidentiality, security, bias awareness, and transparency principles relevant to data labeling and AI workflows.
  • Demonstrated experience delivering high-quality live virtual instruction, ideally to large and diverse audiences.
  • Experience supporting technical curriculum development, lesson refinement, skills labs, or similar instructional content.
  • Strong communication, presentation, empathy, adaptability, and classroom-management skills, with the ability to make complex technical concepts easy to understand.
  • A positive and collaborative mindset, with strong attention to preparation, professionalism, responsiveness, and continuous improvement.
  • Preferred: AWS Certified AI Practitioner (AIF-C01) certification or equivalent expertise, particularly experience aligning training content with certification domains and supporting exam readiness.
Benefits:
  • Remote work: Work remotely from Romania or another location compatible with the required time zone.
  • Part-time contract: Flexible engagement structured around scheduled instructional sessions and program needs.
  • Virtual-first environment: Deliver impactful learning experiences entirely online using modern virtual classroom tools.
  • High-impact teaching: Reach diverse learner populations and contribute to workforce development in AI and data.
  • Professional collaboration: Work alongside program, operations, and instructional teams in an international environment.
  • Curriculum involvement: Contribute ideas and expertise to the development and continuous improvement of technical training content.
  • Potential schedule flexibility: Program dates and lecture times may be adjusted depending on program requirements and instructor availability.
  • Inclusive environment: Participate in a learning culture focused on respect, accessibility, diversity, and equal opportunity.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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