Content Developer: Machine Learning Annotation

Correlation One develops workforce skills for the AI economy

Enterprises and governments work with us to develop talent and close critical data, digital, and technology skills gaps. Our global programs, including training programs and data competitions, also empower underrepresented communities and accelerate careers.

Our mission is to create equal access to the data-driven jobs of the future. We partner with top employers and government organizations to make that a reality, including Amazon, Coca-Cola, Johnson & Johnson, the U.S. State Department, and the U.S. Department of Defense.

Our skills training programs are 100% free for learners and are delivered virtually by industry experts to minimize traditional barriers to career advancement. We take pride in fostering supportive, human-led, group learning environments that build technical proficiency and confidence in participants.

Join us and let's shape the AI Economy together!

Your impact

This is a part-time contract position. The contract is expected to run ~2–4 months, with an anticipated workload of ~10–15 hours per week (may vary based on program needs and consultant capacity).

The Machine Learning Annotation Content Developer will create high-quality instructional materials that teach modern data annotation and labeling workflows used to train and evaluate machine learning systems. The role will develop content across modalities—including text, image, video, audio/speech, and cross-modality labeling—translating real-world annotation tasks into clear, engaging, job-relevant learning experiences.

You will collaborate with our internal program team to produce session plans, hands-on practice, examples, and assessments aligned to defined learning outcomes. Content should model best-in-class annotation behavior: rule-based decisions, clear rationales, consistent application of guidelines, and appropriate handling of ambiguity (e.g., escalation rather than guessing).

A day in the life

• Develop instructional lessons and training materials on:

• Text annotation (e.g., classification, NER, span annotation, summarization evaluation, safety/toxicity, dialogue evaluation)

• Image data annotation (e.g., bounding boxes, polygons, keypoints/landmarks, segmentation basics, quality checks)

• Video labeling (e.g., temporal segments, tracking, event labeling, frame sampling strategies)

• Audio and speech annotation (e.g., transcription conventions, speaker diarization concepts, intent/slot labeling, quality review)

• Cross-modality labeling (e.g., image-text matching, VQA-style labeling, grounding references across modalities)

• Produce complete “content packages” per session/module (as applicable), such as:

• Facilitator guide, learner materials, demos or walkthroughs, practice activities, “strong vs. weak” examples, rubrics/evaluation criteria, and short knowledge checks/assessments

• Create hands-on exercises using a common annotation platform (e.g., Label Studio or similar), including:

• Task setup guidance, labeling instructions, example labels, edge cases, and review workflows

• Review and iterate on content based on internal feedback and peer review

• Participate in weekly and ad hoc meetings with the program team to align on objectives, standards, and delivery constraints.

• Support content deployment into our learning platform (training provided).

Your expertise

Required qualifications

• Demonstrated experience creating machine learning training content, instructional content, curriculum materials, or technical content for adult learners.

• Hands-on experience as a data annotator, including using tools such as Label Studio or similar annotation platforms.

• Ability to translate complex content into clear, learner-friendly lessons with concrete examples.

• Strong command of English (written and verbal) with excellent attention to detail and consistency.

• Organized, deadline-reliable, and comfortable working in a remote, fast-moving environment.

Nice to have

• Experience creating content across multiple data modalities (text, image, video, audio) and/or cross-modality tasks.

• Experience building rubrics, scoring guides, or evaluation criteria for annotation quality.

Where you are

This role is remote and can be located anywhere that is compatible with EST time zone. We are headquartered in New York City and have office space in Midtown Manhattan.

Correlation One’s Commitment

Correlation One is proud to be an Equal Opportunity Employer and is committed to providing equal opportunity for all employees and applicants. Correlation One provides a work environment free of discrimination and harassment. Employment decisions at Correlation One are based solely on business needs, job requirements and individual qualifications, without regard to race, color, religion or belief, national, social or ethnic origin, sex (including pregnancy), age, sexual orientation, gender identity and/or expression, marital, civil union or domestic partnership status, past or present military service, or any other status protected by the laws or regulations in the locations where we operate. We encourage applicants to bring their unique skills, experiences, and outlook to our work environment.

Correlation One is committed to the full inclusion of all qualified individuals. In keeping with our commitment, Correlation One strives to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process. If you need an accommodation to access the job application or interview process, please contact [email protected].

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