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Ankur Roy

Ankur Roy

AI Data Specialist & Technical Evaluator

Talent
KolkataMember since September 11, 2026
Instruction FollowingMulti-Turn DialogueFactuality Verification
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Instruction FollowingMulti-Turn DialogueFactuality Verification

About

Detail-oriented AI Data Specialist and Technical Evaluator with proven production experience across Outlier, Remotasks, and the Atlas Data Annotation platform. Specializes in Reinforcement Learning from Human Feedback (RLHF), multi-turn reasoning critique, complex instruction following, and rigorous factuality verification. Combines engineering analytical rigor with an exceptional eye for detail to train next-generation generative AI foundation models.

Experience

AI Trainer & Evaluation Specialist at Outlier.ai (2024-01 – Present)

  • Evaluate, rank, and rate multi-turn LLM candidate responses across truthfulness, adherence to multi-constraint instructions, conciseness, and tone.
  • Author comprehensive justification rationales diagnosing subtle logical fallacies, edge-case rubric violations, and mathematical inaccuracies.
  • Conduct source-level verification and fact-checking to detect and mitigate subtle hallucinations across STEM and reasoning tasks.
  • Sustain a 95%+ quality audit rating across priority calibration queues and specialized project benchmarks.

Data Annotation Specialist at Atlas Data Annotation Project (2023-01 – 2024-12)

  • Executed fine-grained intent classification, conversational context auditing, and multi-turn dialogue labeling to refine NLU training sets.
  • Evaluated step-by-step reasoning (Chain-of-Thought) outputs, flagging ungrounded inferential leaps or subtle contradictions.
  • Partnered asynchronously with distributed QA reviewers to harmonize edge-case interpretations and standardize scoring rubrics.

AI Data Contributor & Evaluator at Remotasks (2023-01 – 2024-12)

  • Mastered extensive 20+ page dynamic guidelines to deliver high-throughput, high-accuracy text evaluation and taxonomy classification.
  • Identified prompt ambiguities and guideline conflicts, actively providing constructive feedback to project leads to refine edge-case rules.
  • Performed side-by-side preference evaluations to align AI outputs with human safety, helpfulness, and harmlessness policies.

Education

B.Tech in Civil Engineering – Heritage Institute of Technology (2025-06)

Skills

AI Data Specialist & Technical Evaluator

Reviews