ABRAHAM AJIBADE

|

Abraham Ajibade

ABOUT ME

I'm an Artificial Intelligence and Machine Learning Engineer specializing in delivering end-to-end machine learning and AI solutions, while following industry standard MLOps and LLMOps practices. Passionate about creating and driving real-life impact through data.

I thrive at the intersection of development and deployment, building robust MLOps pipelines using industry standard practices and contemporary tools across cloud platforms. Beyond the technical components, I am passionate about breaking down complex questions into simple solutions for stakeholders.

PROFESSIONAL EXPERIENCE

Dec 2024 to Present

Machine Learning Engineer

Northwestern Medicine • Chicago, IL
  • Deployed a high-throughput incident classification system by containerizing a fine-tuned Mixtral 7x8B model via Triton Inference Server on Azure, eliminating 70%+ manual review workload.
  • Established department-wide model deployment framework using ONNX + Triton, resolving cross-backend compatibility for 4+ model families, reducing deployment time by 25%.
  • Spearheaded DevSecOps transformation within Azure DevOps, integrating security automation that remediated 150+ critical vulnerabilities pre-production.
  • Engineered scalable data orchestration layer on Databricks (PySpark/SQL), automating HIPAA-compliant storage and enabling real-time model feedback loops.
  • Productionized medical document summarization microservice with LLMs and Pydantic AI for automated PII redaction and 6th-grade readability conversion.
  • Optimized feature engineering pipelines with parallel PySpark workflows, slashing feature generation latency by 92%.
Triton ONNX Azure VMSS Databricks PySpark LLMs DevSecOps Terraform
May 2023 to Nov 2024

Data Scientist

Blue Lambda Technologies • Atlanta, GA
  • Architected end-to-end ML systems across real estate, retail, and finance domains, delivering PyTorch, XGBoost, and Scikit-Learn models with 95%+ uptime via AWS SageMaker.
  • Co-developed internal RAG platform using LangChain and Qdrant with Gemma 3.4B, resolving 7,000+ weekly employee queries and reducing support tickets by 42%.
  • Owned data engineering backbone for 15+ concurrent models; built robust ETL pipelines on Databricks/AWS EMR with strict data lineage and quality gates.
  • Instituted MLOps monitoring using Arize and MLflow for drift detection, maintaining <5% metrics degradation over 18-month model lifecycles.
  • Championed engineering standards with reproducible Docker/Devcontainer environments and CI/CD automation, reducing technical debt by 60%.
AWS SageMaker PyTorch LangChain Qdrant Databricks MLflow Arize Docker
Jan 2019 to Nov 2020

Data Science Consultant

Upwork & Fiverr • Lagos, Nigeria (Remote)
  • Delivered custom ML solutions (Scikit-learn, XGBoost) for classification and regression, achieving 15% average R² uplift and 22% precision gain aligned to business KPIs.
  • Architected real-time incremental data ingestion using PySpark on AWS EMR, processing 1.5M+ rows with sub-minute latency, reducing data-to-model latency by 87%.
  • Engineered production-grade feature pipelines with automated hyperparameter optimization and SHAP-based explainability for non-technical stakeholders.
  • Refactored legacy Jupyter notebooks into modular, PEP8-compliant packages with 99% test coverage for audit-ready client handoffs.
Scikit-Learn XGBoost PySpark AWS EMR SHAP pytest

EDUCATION

2021 - 2023

Master of Science in Agricultural Economics

University of Kentucky • Lexington, KY

Advanced training in quantitative methods, econometrics, and data analysis. Applied statistical modeling and machine learning techniques to agricultural and economic research problems.

Data Analysis Data Science Econometrics Machine Learning Research Methods Statistical Modeling
2012 - 2017

Bachelor of Science in Agricultural Economics

University of Benin • Benin City, Nigeria

Comprehensive foundation in economics, statistics, and quantitative analysis. Developed strong analytical skills that laid the groundwork for transition into data science and machine learning.

Economics Mathematics Quantitative Analysis Research Methods Statistics

SELECT PROJECTS

Featured

Retail Multimodal Product Discovery Agent

Multimodal product discovery with text, images, or both. Uses BLIP + OpenCLIP embeddings with CrossEncoder re-ranking for precision. Scalable product catalog with fast vector search.

Airflow BLIP FastAPI LangGraph OpenCLIP Qdrant

Human Resources Policy RAG Chatbot

Privacy-first RAG chatbot for context-grounded HR policy answers. Local LLM integration with self-hosted vector database. Zero external API dependencies for data security.

Databricks PDFPlumber LangChain Qdrant RAG

Healthcare Data Mart & ML Pipeline

HIPAA-compliant data mart ingesting 30K records/batch. Fault-tolerant architecture with <2% failure rate. Terraform & Azure DevOps CI/CD—95% fewer manual retries.

Databricks Terraform Azure DevOps PySpark

GitHub Unfollower Agent

AI agent interpreting natural language to manage GitHub connections. Open-Source LLM inference via Ollama with Qdrant vector storage. Deployed on AWS EC2 with Docker & Nginx.

FastAPI LangChain Ollama AWS EC2
View All Projects on GitHub →

SKILLS & TECHNOLOGIES

Languages

Python, SQL, Bash, HCL, Groovy

Machine Learning

PyTorch, Scikit-Learn, XGBoost, PySpark MLlib, ONNX, Deep Learning, NLP, Computer Vision

Generative AI

Large Language Models, LangChain, LangGraph, Prompt Engineering, Retrieval Augmentation Generation, Vector Databases, Model Context Protocol (MCP)

MLOps & Platforms

Docker, Terraform, MLflow, Triton Server, AWS SageMaker, Azure ML, Databricks

Data Engineering

Polars, Pandas, Apache Spark, Apache Airflow, ETL/ELT, SQL

Continuous Integration & Delivery

Azure DevOps, GitHub Actions, Jenkins, GitLab CI/CD, ArgoCD, Docker, Kubernetes, Terraform, Ansible