Jessie Morales

Key Skills

Software

Mercor

CVAT

Other

Top Subject Matter

Computer Science

Mathematics Domain Expertise

LLM Data

Top Data Types

Text

Image

Top Task Types

RLHF

Entity Ner Classification

Segmentation

Classification

Freelancer Overview

Senior Domain Expert Annotator (CS & Mathematics). Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Mercor, Outlier AI, and CVAT. Education includes Doctor of Philosophy, University of Texas at Austin (2020) and Master of Science, Texas A&M University (2016). AI-training focus includes data types such as Text and Image and labeling workflows including RLHF, Entity (NER) Classification, and Segmentation.

Labeling Experience

Senior Domain Expert Annotator (CS & Mathematics)

MercorTextRLHF

I executed advanced data labeling assignments for post-graduate mathematics, algorithmic problem-solving, and software engineering datasets. My work included pairwise comparisons of LLM outputs using multi-dimensional rubrics for factuality and safety, as well as auditing and correcting machine-generated code and proofs. I also led the design of taxonomy guidelines and adversarial red-teaming protocols to reduce domain-specific misclassifications. • Applied RLHF, pairwise comparison, and red teaming for large language model output evaluation • Performed detailed logical and syntactical error tagging on code and mathematical proofs • Developed annotation guidelines to improve accuracy in advanced mathematics datasets • Used proprietary platforms and multi-modal rubrics to enhance LLM guardrails and decrease hallucinations

I executed advanced data labeling assignments for post-graduate mathematics, algorithmic problem-solving, and software engineering datasets. My work included pairwise comparisons of LLM outputs using multi-dimensional rubrics for factuality and safety, as well as auditing and correcting machine-generated code and proofs. I also led the design of taxonomy guidelines and adversarial red-teaming protocols to reduce domain-specific misclassifications. • Applied RLHF, pairwise comparison, and red teaming for large language model output evaluation • Performed detailed logical and syntactical error tagging on code and mathematical proofs • Developed annotation guidelines to improve accuracy in advanced mathematics datasets • Used proprietary platforms and multi-modal rubrics to enhance LLM guardrails and decrease hallucinations

2023 - Present

Specialized Data Labeler & Ontology Designer (Computational Biology)

TextEntity Ner Classification

As the primary subject matter expert for biological data labeling, I annotated scientific literature, medical transcripts, and biochemical pathway diagrams. I developed a customized ontology for genomic sequence interpretation and tags for biological phenomena, then executed and QA'd high-volume batches for accuracy. My role also included performing named entity recognition, sentiment analysis, and relation extraction on peer-reviewed journal datasets. • Designed standardized tags for protein folding anomalies and cellular interactions • Performed entity classification and relation extraction in bioinformatics texts • Maintained 99.8% ground-truth accuracy in QA audits across >10,000 annotations • Utilized Outlier AI's proprietary tools for annotation and quality control

As the primary subject matter expert for biological data labeling, I annotated scientific literature, medical transcripts, and biochemical pathway diagrams. I developed a customized ontology for genomic sequence interpretation and tags for biological phenomena, then executed and QA'd high-volume batches for accuracy. My role also included performing named entity recognition, sentiment analysis, and relation extraction on peer-reviewed journal datasets. • Designed standardized tags for protein folding anomalies and cellular interactions • Performed entity classification and relation extraction in bioinformatics texts • Maintained 99.8% ground-truth accuracy in QA audits across >10,000 annotations • Utilized Outlier AI's proprietary tools for annotation and quality control

2021 - 2024

Multimodal Data Annotator & QA Specialist

CVATImageSegmentation

I specialized in multimodal data annotation for computer vision projects, using CVAT for semantic segmentation, point-cloud annotation, and bounding boxes for biomedical imaging. I also categorized audio and text data to support NLU models through accurate transcription and formatting. Optimization of platform workflows and bug reporting enhanced overall annotation efficiency and speed. • Labeled MRI and histology images using segmentation and bounding box approaches • Supported SFT projects involving transcription and categorization of audio/text data • Identified/communicated annotation platform UI bugs to engineering teams • Maintained top 1% ranking in speed/accuracy across multiple projects

I specialized in multimodal data annotation for computer vision projects, using CVAT for semantic segmentation, point-cloud annotation, and bounding boxes for biomedical imaging. I also categorized audio and text data to support NLU models through accurate transcription and formatting. Optimization of platform workflows and bug reporting enhanced overall annotation efficiency and speed. • Labeled MRI and histology images using segmentation and bounding box approaches • Supported SFT projects involving transcription and categorization of audio/text data • Identified/communicated annotation platform UI bugs to engineering teams • Maintained top 1% ranking in speed/accuracy across multiple projects

2020 - 2021

Graduate Researcher & Data Specialist

OtherImageClassification

I collected, cleaned, and labeled large-scale transcriptomic and microscopy image datasets for machine learning model input as part of academic research. I developed custom GUIs to accelerate image labeling workflows and supervised batch processing by laboratory assistants. My responsibilities included preprocessing, normalization, and ensuring data quality prior to inclusion in algorithmic pipelines. • Labeled cellular microscopy images and transcript data for predictive ML • Built and implemented custom annotation interfaces for manual data entry • Supervised labeling workflows and conducted batch QA on scientific datasets • Performed all preprocessing and formatting for experimental data ingestion

I collected, cleaned, and labeled large-scale transcriptomic and microscopy image datasets for machine learning model input as part of academic research. I developed custom GUIs to accelerate image labeling workflows and supervised batch processing by laboratory assistants. My responsibilities included preprocessing, normalization, and ensuring data quality prior to inclusion in algorithmic pipelines. • Labeled cellular microscopy images and transcript data for predictive ML • Built and implemented custom annotation interfaces for manual data entry • Supervised labeling workflows and conducted batch QA on scientific datasets • Performed all preprocessing and formatting for experimental data ingestion

2016 - 2020

Education

Work History