Mohammed M.

Key Skills

Software

Argilla

Axiom AI

Clickworker

Top Subject Matter

Biomedical/pap smear image analysis for cervical cancer screening

Biomedical/knowledge graph-style AI enrichment and multimedia analysis

AI for biomedical therapy optimization using knowledge graphs

Top Data Types

Image

Audio

Document

Top Task Types

Diagnosis

Entity (NER) Classification

Classification

Segmentation

Polyline

Freelancer Overview

Python AI Engineer — Cancer screening AI system (CNN-based detection/classification). Brings 8+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include TensorFlow, Neo4j, and Python. Education includes Bachelor of Science, Addis Ababa Science and Technology University (2019). AI-training focus includes data types such as Medical, DICOM, and Computer Code and labeling workflows including Diagnosis, Entity (NER) Classification, and Computer Programming.

Labeling Experience

Python AI Engineer — Biomedical therapy design and treatment optimization project

Worked on transforming therapy design and treatment optimization using advanced AI tools over large-scale biomedical knowledge graph data. Developed and used Python-based AI techniques to analyze biomedical data and uncover insights that support personalized treatment planning. Contributed to improved precision and effectiveness of medical interventions by optimizing therapy recommendations. • Applied AI algorithms in Python for biomedical data analysis and insight discovery. • Supported authoring/packaging/deployment of AI components for biomedical research use. • Produced personalized treatment plan outputs based on patient characteristics. • Focused on treatment optimization and improved medical outcome metrics.

2023 - 2025

Python AI Engineer — Cancer screening AI system (CNN-based detection/classification)

Diagnosis

Served as a Python AI Engineer for a cervical cancer screening AI system that analyzes pap smear images and supports clinical decision assistance. Built features for generating interactive data reports with visual graphs and added the capability to export reports as PDF files. Developed a CNN model with 96% efficiency for detecting and classifying cervical cancer to aid earlier detection and improved outcomes. • Prepared/processed image-based inputs for medical AI workflows in Python. • Used TensorFlow and related Python libraries for model development and numerical computation. • Implemented backend/API functionality using Django for report generation and model-serving needs. • Validated impact via reported improvements in user satisfaction by 30%.

2023 - 2025

AI Mobile Developer — People Intelligence (Neo4j + ML embeddings + enrichment)

Entity (NER) Classification

Contributed to AI and graph intelligence features for a People Intelligence system that uses multimedia analysis and knowledge-enriched entity linking. Implemented machine learning pipelines to analyze multimedia (audio/video/image) and connected enriched knowledge to entities using Wikipedia and synonym retrieval. Developed backend APIs to ingest and retrieve relationship data from a Neo4j knowledge graph and deployed the system for scalable usage. • Modeled complex relationships between people, locations, and multimedia metadata in Neo4j using Cypher. • Integrated LlamaIndex PropertyGraphIndex with Gemini-based ML embeddings for graph intelligence. • Built AI-driven enrichment for entity linking using Wikipedia and synonyms. • Containerized and deployed the platform on Google Cloud with Docker/Docker Compose and CI/CD integration.

2022 - 2024

Education

Work History