Selena A.

Key Skills

Software

No software listed

Top Subject Matter

AI-generated Code Review and LLM Evaluation

NLP and Model Output Annotation

Computer Vision and Image Annotation

Top Data Types

Text

Image

Top Task Types

RLHF

Classification

Entity (NER) Classification

Freelancer Overview

AI-generated Code Reviewer and LLM Evaluation Lead. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Science, University of Washington, Seattle (2018). AI-training focus includes data types such as Computer Code, Programming, and Text and labeling workflows including Evaluation, Rating, and RLHF.

Labeling Experience

AI-generated Code Reviewer and LLM Evaluation Lead

Led comprehensive AI-generated code review for LLM training datasets, focusing on quality, correctness, and best practices. Developed and utilized an internal LLM evaluation framework to assess model output alignment and effectiveness. Oversaw annotation workflow management and quality assurance for code-based data labeling. • Evaluated AI-generated Python and JavaScript code for accuracy and adherence to guidelines. • Managed dashboards for ML annotation workflow and QA tracking. • Contributed to model alignment efforts for improved LLM outputs. • Provided subject matter expertise in code reviewing for AI training.

2022 - Present

Data Annotation Lead—RLHF and NLP

TextRLHF

Led data annotation initiatives for NLP training datasets, participating in RLHF feedback cycles for model-generated code and content. Rated model outputs and provided expert feedback during reinforcement learning from human feedback loops. Guided annotation teams in following established guidelines for text-based AI training. • Provided detailed ratings of model-generated responses. • Performed expertise-driven feedback for AI alignment. • Oversaw annotation processes for NLP datasets. • Contributed to continual improvement of model behavior and output quality.

2020 - 2021

Code Data Annotator—ML Training

Annotated and labeled code generation datasets, contributing examples and assessments for AI model training. Evaluated and categorized machine-generated code samples based on correctness and style. Worked closely with ML teams to ensure datasets represent diverse coding scenarios and edge cases. • Categorized generated code for training labeling tasks. • Provided human feedback on code correctness and clarity. • Generated code snippets for annotation and RLHF cycles. • Improved dataset coverage for programming language models.

2018 - 2020

NLP Data Annotator—Entity Recognition

TextEntity (NER) Classification

Labeled and annotated text samples for NLP and AI model training, focusing on entity recognition and document classification tasks. Worked within an ML team to ensure annotation consistency and guideline adherence. Helped define best practices for text annotation across different projects. • Labeled and classified named entities in text samples. • Assisted in building gold-standard NLP datasets. • Coordinated with other annotators for quality control. • Supported research efforts with accurate and reliable data labels.

2018 - 2020

Image Annotation Specialist—Computer Vision

ImageClassification

Annotated and labeled over 50,000 samples for computer vision models, including classification and image-level feature tagging. Collaborated with ML researchers to define and refine annotation guidelines ensuring dataset quality. Utilized custom internal tools for efficient image labeling and quality control. • Prepared and organized image datasets for machine learning experiments. • Maintained high standard of accuracy in image classification tasks. • Worked closely with research teams for iterative guideline development. • Enabled downstream computer vision model evaluation and training.

2018 - 2020

Education

Work History