About the role
We are seeking experienced in Biology help evaluate and enhance large language model (LLM) outputs related to nutrition, dietary habits, and healthy eating. You’ll assess AI-generated content for scientific accuracy, safety, and relevance — contributing to the development of responsible AI in nutrition and wellness. Selected talents will label and evaluate data related to food intake, dietary patterns, and nutrition information to support AI models focused on nutrition tracking, coaching, or research. Main tasks listed: Annotate food items, portion sizes, meal composition, and nutrient content from text, images, or logs; Classify dietary patterns (e.g., macronutrient balance, meal timing, dietary restrictions/preferences); Verify accuracy of nutritional data against trusted references (e.g., food composition databases); Identify and flag mislabeled, inconsistent, or culturally ambiguous food entries.
Experience
Background in nutrition, dietetics, food science, or a related field; Familiarity with food composition databases and dietary assessment methods; Strong attention to detail, especially with portion estimation and food categorization; Comfort working with annotation tools, spreadsheets, or structured data formats; Ideal to have a MacBook
Selection process
Apply through the official Turing page (free account required). The listing describes this selection process: Shortlisting based on qualifications and one round of interview.
Eligibility
Not stated on the listing (remote)