$11.50 - $15.50/hr
... video, and how these capabilities influence annotation and evaluation tasks. * Knowledge of ... Benefits: * Remote work: Work remotely from Romania or another location compatible with the ...
$11.50 - $15.50/hr
... video, and how these capabilities influence annotation and evaluation tasks. * Knowledge of ... Benefits: * Remote work: Work remotely from Romania or another location compatible with the ...
Remote Video Annotation information
What is remote video annotation?
Remote video annotation is the process of labeling or tagging objects, actions, or events in video footage while working from a location outside of a traditional office, typically from home. Annotators use specialized software tools to draw boxes, create masks, or assign labels to specific frames or sequences in videos. This annotated data is essential for training and improving computer vision models used in applications like self-driving cars, security systems, and entertainment technology. Remote video annotation jobs offer flexibility, but often require attention to detail, strong computer skills, and the ability to follow detailed guidelines.
What are the typical daily tasks and challenges faced by a remote video annotation specialist?
As a Remote Video Annotation specialist, your daily tasks typically include reviewing video footage, accurately labeling objects or actions according to specific guidelines, and ensuring data consistency for machine learning projects. One common challenge is maintaining high attention to detail over long periods, as precise annotations are crucial for training effective AI models. Additionally, you'll often collaborate with project managers or quality assurance teams to clarify requirements, discuss edge cases, and receive feedback. Flexibility and good time management are important, as workloads can vary based on project deadlines and client needs.
What are the key skills and qualifications needed to thrive as a remote video annotation specialist?
To excel as a Remote Video Annotation Specialist, you need strong attention to detail, visual accuracy, and basic computer literacy, often supported by prior experience in data labeling or related fields. Familiarity with annotation platforms (such as CVAT or Labelbox) and understanding of video formats and metadata are typically required. Effective time management, reliability, and clear communication help specialists meet deadlines and collaborate remotely. These skills ensure precise data labeling, which is crucial for training high-performing AI and machine learning models.
What is the difference between Remote Video Annotation vs Remote Data Labeling?
| Aspect | Remote Video Annotation | Remote Data Labeling |
|---|---|---|
| Primary Focus | Annotating objects, actions, and events in videos | Labeling data across various formats, including images, text, and videos |
| Work Environment | Remote, often collaborative with video review tools | Remote, using labeling platforms for different data types |
| Required Skills | Attention to detail, understanding of video content | Accuracy, familiarity with labeling tools |
Remote Video Annotation specifically involves marking objects and actions within videos, while Remote Data Labeling covers a broader range of data types, including images and text. Both roles require attention to detail and remote work skills, but Video Annotation focuses on video content analysis, making it more specialized within the data labeling industry.
What are the most commonly searched types of Video Annotation jobs in Missouri?
The most popular types of Video Annotation jobs in Missouri are:
What are popular job titles related to Remote Video Annotation jobs in Missouri?
For Remote Video Annotation jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Remote Video Annotation jobs in Missouri look for?
The top searched job categories for Remote Video Annotation jobs in Missouri are:
What cities in Missouri are hiring for Remote Video Annotation jobs?
Cities in Missouri with the most Remote Video Annotation job openings:
Lead Instructor: Machine Learning Data Associate
Remote
Jobgether
$11.50 - $15.50/hr
Full-time
This job post has expired today. Applications are no longer accepted.
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!
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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