Job Description

Key Responsibilities

Curate, clean, and label datasets for training and fine?tuning AI/ML models (structured, text, image, audio, or conversation data depending on use case). Design and maintain annotation guidelines, taxonomies, and labeling schemes that reflect product and business logic. Run quality checks on annotated data to ensure consistency, accuracy, and low bias. Evaluate model outputs (e.g., chat responses, classifications, recommendations), score quality, and identify error patterns and edge cases. Provide detailed feedback and examples to help data scientists/ML engineers refine models and prompts. Collaborate with product managers and domain experts to understand use cases, compliance constraints, and desired AI behaviours. Help set up and monitor training and evaluation pipelines (experiments, A/B tests, benchmark suites). Document training procedures, annotation standards, and evaluation criteria for internal reuse. Stay updated on AI and ML best practices, with a focus on data quality, safety, and responsible AI. Where required, support internal training for non?technical teams on how to interact with, test, and give feedback to AI systems.
Required Skills & Experience

2-5 years of experience in one or more of: data annotation/labeling, NLP/chatbot training, ML model evaluation, data analytics, or a related role. Strong analytical skills and ability to work with large data sets (Excel/Sheets; preferably SQL or basic Python/R for analysis). Excellent language and communication skills; able to judge clarity, correctness, and tone of AI outputs (especially for text?based systems). High attention to detail and consistency in following and refining guidelines. Experience collaborating with data scientists/ML engineers and product teams. Understanding of basic machine learning concepts (training data, validation, overfitting, bias, evaluation metrics).
Nice?to?Have

Hands?on exposure to annotation tools, prompt?management tools, or labeling platforms. Experience working with or around large language models (LLMs), chatbots, recommendation systems, or search relevance. Domain knowledge in one or more relevant areas (for example: HR, healthcare, finance, education, customer support) if your AI is domain?specific. Familiarity with responsible AI topics: bias, fairness, safety, and privacy.
Education

Bachelor's degree in Computer Science, Data Science, Engineering, Linguistics, Psychology, or any quantitative/analytical discipline. Equivalent practical experience is also acceptable if you demonstrate strong data and evaluation skills.
Job Type: Full-time

Pay: ?8,086.00 - ?38,761.31 per month

Work Location: In person