Male Fertility Data Annotation

The work

You will review and correct annotations used to train an AI-assisted semen analyzer. The work takes place in an annotation platform and focuses on reconstructed grayscale microscopy videos, not standard phase-contrast or brightfield images.

You will receive a short paid onboarding session explaining how sperm appear in this imaging method. You will also write brief notes about unclear cells, image-quality problems, and questions about the annotation guideline.

• Check rotated bounding boxes around individual sperm in grayscale microscopy frames.
• Add missed sperm, remove false positives such as debris, round cells, and artefacts, and correct box orientation.
• Watch video sequences of about two seconds and confirm or correct progressive, non-progressive, and immotile classifications under WHO 6th-edition 2021 categories.
• Count sperm in defined regions when requested and compare the counts with model output.
• Possibly review sperm morphology involving the head, midpiece, and tail using Kruger and WHO-strict criteria in a later feasibility phase.

What it pays and takes

This is a contractor role for experienced semen-analysis professionals. The work requires careful, consistent visual review and close adherence to a written guideline.

• Pay: $6 to $14 USD per hour.
• Experience: at least two years of hands-on manual semen analysis in a clinical andrology, IVF, or reproductive-medicine laboratory.
• Required experience includes concentration testing with a hemocytometer and motility grading under the WHO 5th or 6th edition.
• Language: fluent written English for notes and guideline questions.
• Equipment: reliable internet and a desktop or laptop with a screen of at least 1080p. Phones and tablets cannot be used.
• Application materials: a CV and verifiable proof of laboratory experience, including employer, role, and dates.
• You must be willing to sign an NDA, IP assignment, and data-protection agreement before receiving access.
• Open to candidates in eligible countries. Your country of residence is required for the data-protection review.
• Preferred: an embryology or andrology credential, EQA or proficiency-testing participation, Kruger strict morphology experience, CASA experience, or experience with Label Studio, Encord, CVAT, V7, or a similar annotation tool.

Before production work

Before production labeling, you will complete a paid calibration task lasting about two to three hours. Your work is scored against expert reference labels, and agreement with those references is reviewed regularly afterward.

You will receive brief guideline training and confirm completion in a short signed training record.

• All work stays inside the annotation platform.
• Do not download, screenshot, or copy project images.
• Do not use AI tools or third parties with project data.
• The data is de-identified research data, and you must not try to identify any participant.

How it works

Apply on OpenTrain and include the details needed to review your experience. OpenTrain reviews applications there.

• Describe the laboratories where you worked, your years of experience, approximate work volume, and the WHO edition you used.
• List your credentials and any EQA or proficiency-testing participation.
• Provide your weekly availability and time zone.
• Provide your country of residence for the data-protection review.

About AI training work

OpenTrain is the hiring and contracting organization for this role. AI training work uses human-reviewed examples, such as labeled images and videos, to help AI systems recognize patterns and produce more reliable results; experienced reviewers are needed when accuracy depends on clinical knowledge.

Where you can work

This role is 100% remote: you can work from any country except Andorra, Afghanistan, Barbados, Burkina Faso, Burundi, Brazil, Belarus, Belize, DR Congo, Central African Republic, Congo (Republic), Cameroon, China, Cuba, Cape Verde, Djibouti, Dominica, Eritrea, Fiji, Micronesia, Grenada, Georgia, Guinea, Equatorial Guinea, Guinea-Bissau, Honduras, Haiti, Iraq, Iran, Kyrgyzstan, Kiribati, Comoros, St. Kitts and Nevis, North Korea, Lebanon, Liberia, Lesotho, Libya, Montenegro, Marshall Islands, Mali, Myanmar, Mauritania, Maldives, Malawi, Nicaragua, Nepal, Nauru, Papua New Guinea, Palestine, Palau, Russia, Solomon Islands, Seychelles, Sudan, Sierra Leone, Somalia, Suriname, South Sudan, São Tomé and Príncipe, Syria, Eswatini, Chad, Togo, Tajikistan, Timor-Leste, Turkmenistan, Tonga, Tuvalu, Ukraine, Uganda, Vatican City, St. Vincent and Grenadines, Venezuela, Vanuatu, Samoa, Yemen, Zambia and Zimbabwe.