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Data Annotation Tech
Labelbox
Remotasks
SuperAnnotate
Document
Computer Code Programming
Text
Data Collection
Computer Programming/Coding
RLHF
Evaluation/Rating
Fine-tuning
Function Calling
Prompt + Response Writing (SFT)AI Data Engineer, Turing (Contract, Remote). Brings 7+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Other. Education includes Master of Science, WorldQuant University (2022) and Bachelor of Science, University of Lagos (2020). AI-training focus includes data types such as Computer Code and Programming and labeling workflows including Evaluation, Rating, and Data Collection.
Computer Code ProgrammingRLHFDesigned and evaluated multi-step agent tasks for large language model training, including prompt engineering, trajectory analysis, rubric development, and safety failure annotation across multiple model comparisons.
Computer Code ProgrammingFunction CallingEvaluated LLM outputs across multiple structured AI test campaigns by scoring responses against defined rubrics and strict quality thresholds. Built repeatable evaluation workflows to assess response correctness and integration quality for function-calling and coding-style tasks. Used quantitative metrics to understand model performance and guide improvements for future iterations. • Function-calling API evaluation • SWE benchmark-style code evaluation • Rubric-based scoring with quality thresholds • Performance measurement using precision, recall, and F1
Computer Code ProgrammingData CollectionDesigned multi-step task workflows to generate high-quality training data intended for improving LLM integration accuracy. Produced datasets iteratively, refining outputs to meet maximum evaluation scores for sensitive projects. Focused on producing training-ready examples aligned to downstream model behavior requirements. • Multi-step training data generation workflows • Iterative improvement of dataset quality • Training data for LLM integration accuracy • Emphasis on high evaluation scores
Mentored learners through applied projects and microlearning-style instruction to strengthen programming foundations. Supported students building chatbot and automation-style projects, providing guidance that functioned as an AI tutoring/training activity. Encouraged project-based learning and iterative improvement of student outcomes. • Taught Python and Scratch to ages 8–17 • Mentored chatbot and bot-building projects • Guided applied programming assignments • Provided mentoring for iterative student development
Master of Science, Financial Engineering
Bachelor of Science, Electrical and Electronics Engineering
Computer Technical SwarmBench Expert
Data Engineer (Freelance)
