You will help improve AI systems that work with nutrition, dietary habits, and healthy eating information. The work involves reviewing AI-generated content for scientific accuracy, safety, and relevance, then labeling dietary data used in nutrition tracking, coaching, and research applications.
- Annotate food items, portion sizes, meal composition, and nutrient content from text, images, or food logs.
- Classify dietary patterns, including macronutrient balance, meal timing, dietary restrictions, and food preferences.
- Check nutritional data against trusted food composition databases and other appropriate references.
- Find mislabeled, inconsistent, or culturally ambiguous food entries.
- Apply and refine annotation guidelines for different cuisines and dietary contexts.
- Maintain consistent quality across large batches of labeled data.
What It Pays And Takes
This is an entry-level contractor and freelance assignment for people with relevant biology, nutrition, dietetics, food science, or related experience. The work is remote and flexible, with the engagement planned for eight weeks.
- Pay: No rate or fixed payment is provided in the listing.
- Time: 20+ hours per week.
- Location: Remote and open worldwide.
- Language: English proficiency is required.
- Required background: Nutrition, dietetics, food science, biology, or a related field.
- Required skills: Familiarity with food composition databases and dietary assessment methods.
- Required skills: Careful portion estimation, food categorization, and review of nutrition content for scientific accuracy, safety, and relevance.
- Required tools: Comfort with annotation tools, spreadsheets, or structured data formats.
- Helpful: A Registered Dietitian credential or equivalent qualification.
- Helpful: Experience with multilingual or multicultural food data, machine-learning data labeling, or AI training work.
- Helpful: Access to a MacBook.
How It Works
Apply on OpenTrain with your resume, then complete the application on the hiring site.
About AI Training Work
AI training is the human work behind systems that learn from examples. People label information and review model outputs so AI can produce more accurate and useful results, and subject-matter experts help assess specialized content such as nutrition data.