Sunday Olamide

Key Skills

Software

Mindrift

Top Subject Matter

LLM Calibration

Rlhf Domain Expertise

Code Evaluation

Top Data Types

Text

Video

Computer Code Programming

Top Task Types

Classification

RLHF

Evaluation Rating

Computer Programming Coding

Text Generation

Fine Tuning

Function Calling

Freelancer Overview

AI Principal Backend Calibrator, Amazon BigCode Project. Brings 9+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Mindrift. Education includes Bachelor of Science, Oduduwa University. AI-training focus includes data types such as Computer Code, Programming, and Text and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

AI Team Lead Engineer, Microsoft Project

Classification

As AI Team Lead Engineer for a Microsoft Project, I built taxonomy-to-dataset pipelines and led metadata taxonomy design across multiple dataset iterations. I enforced annotation guidelines, conducted daily reviews, and collaborated with engineers and trainers to deliver curated datasets. My responsibilities included LLM calibration, validation, and improving evaluation metrics for targeted flows. • Designed and maintained L1/L2/L3 metadata structures with automated validators. • Oversaw daily annotation reviews and IRR compliance in the labeling tool. • Coached trainers and coordinated with engineers for dataset delivery. • Operated calibration pipelines and improved win-rate and task completion metrics.

As AI Team Lead Engineer for a Microsoft Project, I built taxonomy-to-dataset pipelines and led metadata taxonomy design across multiple dataset iterations. I enforced annotation guidelines, conducted daily reviews, and collaborated with engineers and trainers to deliver curated datasets. My responsibilities included LLM calibration, validation, and improving evaluation metrics for targeted flows. • Designed and maintained L1/L2/L3 metadata structures with automated validators. • Oversaw daily annotation reviews and IRR compliance in the labeling tool. • Coached trainers and coordinated with engineers for dataset delivery. • Operated calibration pipelines and improved win-rate and task completion metrics.

2025 - 2025

AI Full-Stack Engineer & LLM Trainer, Apple & ServiceNow projects

As AI Full-Stack Engineer & LLM Trainer for Apple & ServiceNow projects, I developed pipelines for algorithmic data curation and hard negative probing on code and UI flows. This included building and evaluating LLM-driven UIs, safe parallelism, structured error taxonomy, and audit logging for platform reliability. My training cycles led to measurable gains in completion and platform performance. • Built training/evaluation flows with Python and JavaScript frameworks. • Completed over 400 LLM training and evaluation cycles. • Created reusable UI patterns and a lightweight evaluation harness. • Executed function calling and parallelism workflow enhancements for annotation strength.

As AI Full-Stack Engineer & LLM Trainer for Apple & ServiceNow projects, I developed pipelines for algorithmic data curation and hard negative probing on code and UI flows. This included building and evaluating LLM-driven UIs, safe parallelism, structured error taxonomy, and audit logging for platform reliability. My training cycles led to measurable gains in completion and platform performance. • Built training/evaluation flows with Python and JavaScript frameworks. • Completed over 400 LLM training and evaluation cycles. • Created reusable UI patterns and a lightweight evaluation harness. • Executed function calling and parallelism workflow enhancements for annotation strength.

2024 - 2025

AI Principal Backend Calibrator, Amazon BigCode Project

As AI Principal Backend Calibrator for the Amazon BigCode Project, I developed backend evaluation pipelines supporting A/B testing and large-scale LLM calibration. I collaborated with engineering teams to deliver labeling pipelines with IRR and QA gates, and merged RLHF data into a unified schema for improved benchmarks. This role involved preference tuning, multilingual evaluation, and monitoring production stability under heavy load. • Built and managed data pipelines for class balance, drift, and duplicate validation. • Implemented CI quality gates to ensure test coverage of all pipelines. • Conducted hard negative sampling and preference data merging for RLHF workflows. • Collaborated with teams on labeling workflows and ensured timely project delivery.

As AI Principal Backend Calibrator for the Amazon BigCode Project, I developed backend evaluation pipelines supporting A/B testing and large-scale LLM calibration. I collaborated with engineering teams to deliver labeling pipelines with IRR and QA gates, and merged RLHF data into a unified schema for improved benchmarks. This role involved preference tuning, multilingual evaluation, and monitoring production stability under heavy load. • Built and managed data pipelines for class balance, drift, and duplicate validation. • Implemented CI quality gates to ensure test coverage of all pipelines. • Conducted hard negative sampling and preference data merging for RLHF workflows. • Collaborated with teams on labeling workflows and ensured timely project delivery.

2024 - 2025

Senior Software Engineer, Mindrift

MindriftText

At Mindrift as a Senior Software Engineer, I rebuilt the labeling tool backend and integrated LLM workflows including rubric-driven evaluations. I deployed LLMs with prompt validation for rubric and guideline compliance, achieving high conformance in final evaluations. My role encompassed designing training and evaluation pipelines, optimizing metrics, and supporting reliable data annotation environments. • Engineered Flask microservices and async I/O for scalable evaluations. • Integrated LangChain and LangGraph for multi-tool annotation flows. • Delivered robust APIs enabling real-time metrics and idempotent operations. • Developed win-rate dashboards and optimized system latency for training pipelines.

At Mindrift as a Senior Software Engineer, I rebuilt the labeling tool backend and integrated LLM workflows including rubric-driven evaluations. I deployed LLMs with prompt validation for rubric and guideline compliance, achieving high conformance in final evaluations. My role encompassed designing training and evaluation pipelines, optimizing metrics, and supporting reliable data annotation environments. • Engineered Flask microservices and async I/O for scalable evaluations. • Integrated LangChain and LangGraph for multi-tool annotation flows. • Delivered robust APIs enabling real-time metrics and idempotent operations. • Developed win-rate dashboards and optimized system latency for training pipelines.

2023 - 2025

Education

Work History