Sharif Y.

Key Skills

Software

AWS SageMaker

Appen

CrowdFlower

CrowdSource

Data Annotation Tech

Dataturk

Img Lab

Labelbox

LabelImg

Label Studio

LightTag

OpenCV AI Kit (OAK)

Clickworker

Dataloop

Datatroniq

Datumbox

Datasaur

Datature

Deep Systems

Doccano

Encord

Figure Eight

Google Cloud Vertex AI

Humanatic

Kili Technology

Micro1

Mercor

Mighty AI

Mindrift

OneForma

Playment

Redbrick AI

Prodigy

Roboflow

Sama

Remotasks

Top Subject Matter

Healthcare documents

NLP classification

and clinical/administrative records

Top Data Types

Text

Computer Code Programming

Document

Top Task Types

Classification

Entity (NER) Classification

Cuboid

Object Detection

Text Generation

Question Answering

Text Summarization

RLHF

Red Teaming

Transcription

Evaluation/Rating

Computer Programming/Coding

Function Calling

Prompt + Response Writing (SFT)

Data Collection

Point/Key Point

Freelancer Overview

Senior Software Engineer, UnitedHealth Group (NLP document processing and productionization of ML models). Brings 9+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Science, The University of Texas at Austin (2018). AI-training focus includes data types such as Document, Computer Code, and Programming and labeling workflows including Classification, Evaluation, and Rating.

Labeling Experience

Senior Software Engineer, UnitedHealth Group (NLP document processing and productionization of ML models)

DocumentClassification

Designed and implemented NLP-driven document processing capabilities that improved automated classification accuracy for clinical and administrative records. Built and automated data validation and transformation pipelines to support analytics and AI initiatives. Collaborated with data science teams to productionize PyTorch-based machine learning models within service architectures. • Ingested and processed unstructured clinical/administrative documents for downstream ML • Improved model-driven classification performance through workflow integration • Supported analytics/AI by transforming validated data into model-ready formats • Worked alongside ML teams to deploy and integrate trained models into existing services

2022 - 2026

Software Engineer, GE HealthCare (ML/NLP feature development and evaluation support)

Contributed to early-stage machine learning and NLP feature development for intelligent healthcare data processing workflows. Supported PyTorch experimentation and model evaluation activities in an engineering environment. Built and optimized preprocessing and validation workflows to improve downstream analytics accuracy. • Developed and supported NLP/ML features for healthcare data processing • Performed or supported model evaluation workflows using PyTorch • Automated data preprocessing/validation for improved analytics outcomes • Implemented secure REST endpoints supporting internal automation and reporting for ML-adjacent workflows

2018 - 2019

Education

Work History