$11.50 - $15.50/hr
... online environment. You will also contribute to curriculum refinement and continuous course ... Explain how data collection, annotation, labeling decisions, model training, evaluation, and ...
$11.50 - $15.50/hr
... online environment. You will also contribute to curriculum refinement and continuous course ... Explain how data collection, annotation, labeling decisions, model training, evaluation, and ...
Online Data Annotation information
See Missouri salary details
$5.23 - $9
4% of jobs
$9 - $12.77
13% of jobs
$13.63 is the 25th percentile. Wages below this are outliers.
$12.77 - $16.54
36% of jobs
$16.54 - $20.31
20% of jobs
$21.15 is the 75th percentile. Wages above this are outliers.
$20.31 - $24.07
11% of jobs
$24.07 - $27.84
9% of jobs
$27.84 - $31.61
5% of jobs
$31.61 - $35.38
1% of jobs
$35.38 - $39.15
0% of jobs
$39.15 - $42.92
0% of jobs
$42.92 - $46.68
1% of jobs
$5
$21
$46
How much do online data annotation jobs pay per hour?
As of Aug 23, 2026, the average hourly pay for online data annotation in Missouri is $21.76, according to ZipRecruiter salary data. Most workers in this role earn between $13.82 and $21.77 per hour, depending on experience, location, and employer.
What is an online data annotation?
An Online Data Annotation job involves labeling, tagging, or categorizing data such as images, text, audio, or video to help improve machine learning models. Annotators follow guidelines to ensure accuracy and consistency, making AI systems more effective. This work is typically done remotely and requires attention to detail. Many companies use data annotation to train AI applications like chatbots, image recognition software, and search engines.
What does an online data annotation do?
As an Online Data Annotation specialist, your day will usually involve reviewing various types of data—such as images, text, or audio—and carefully applying labels or tags according to strict guidelines provided by clients or team leads. Most positions are remote and individual-focused, allowing flexibility in managing your workflow, though you may regularly communicate with supervisors for feedback or updates. Deadlines and productivity targets are common, so staying organized and focused on accuracy is crucial. Over time, you may have opportunities to work on more complex annotation projects or take on quality assurance responsibilities, supporting your professional growth in the data and AI sectors.
What are the key skills and qualifications needed to thrive in online data annotation, and why are they important?
To thrive as an Online Data Annotation professional, you need strong attention to detail, excellent reading comprehension, and basic computer proficiency, often demonstrated through a high school diploma or equivalent. Familiarity with annotation platforms, data labeling tools, and occasionally frameworks like Labelbox or Prodigy is valuable, though on-the-job training is commonly provided. Outstanding time management, adaptability, and the ability to follow precise guidelines will help you excel in this role. These skills and qualities ensure accurate, high-quality data labeling that powers AI and machine learning applications.
What are the most commonly searched types of Data Annotation jobs in Missouri?
The most popular types of Data Annotation jobs in Missouri are:
What are popular job titles related to Online Data Annotation jobs in Missouri?
For Online Data Annotation jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Online Data Annotation jobs in Missouri look for?
The top searched job categories for Online Data Annotation jobs in Missouri are:
$11.50 - $15.50/hr
Full-time
Posted 11 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.
- 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.
- 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!
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