ARTIFICIAL INTELLIGENCE | MACHINE LEARNING ENGINEER · LOUISVILLE METROPOLITAN AREA

Abraham Ajibade

From ideation to production, done right.

Artificial Intelligence Engineer Machine Learning Engineer Data Engineer
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Profile

Production systems, thoughtfully operated.

I architect, deploy, and operate production Artificial Intelligence systems across healthcare, finance, and retail. My work spans high-performance model serving, generative artificial intelligence (GenAI), machine learning operations (MLOps), and cloud-native data platforms.

Tools I work with

Skills

Observability & Monitoring

Application ObservabilityInfrastructure MetricsApplication InstrumentationPrometheusGrafanaArize AIMLflowTempoRequest TracingModel MonitoringDrift DetectionGround Truth Performance Monitoring

Model Delivery & Operations

DockerKubernetesMLflowTritonAWS SageMakerAWS BedrockAzure FoundryAzure Machine LearningDatabricks

Machine Learning & Model Development

PyTorchScikit-LearnXGBoostPySpark MLlibONNXDeep LearningNLPComputer Vision

Generative AI

Large Language ModelsLangChainLangGraphPrompt EngineeringRetrieval Augmented GenerationSemantic KernelVector DatabasesModel Context Protocol

Data Engineering

PolarsPandasApache SparkApache AirflowLuigiETL/ELTSQL

Cloud & Platform Engineering

TerraformDatabricks Asset BundlesAnsibleGitAWSAzureGCP

Deployment Integration & Delivery

GitHub ActionsJenkinsDrone CIArgoCDGitHubAzure DevOpsAWS CodeBuild

What I've done

Selected work

Artificial Intelligence Endpoint Observability Dashboard

Production observability for Triton-served Artificial Intelligence endpoints, combining endpoint traffic and performance data with Kubernetes infrastructure health. The dashboard is actively used to monitor services and trigger alerts when issues arise.

Triton metricsEndpoint & infrastructure healthAlerts

Retail Chat Agent Backend

Artificial Intelligence-powered product discovery that lets shoppers search with natural-language descriptions or photos. I integrated OpenCLIP, BLIP, text embeddings, and vector search behind FastAPI on AWS.

Text + imageMultimodal retrievalRelevant results
AWS BLIP FastAPI LangGraph LiteLLM OpenAI CLIP PyTorch Qdrant
View on GitHub

Retail Chat Agent MCP Server

A Model Context Protocol server that gives multimodal agents real-time product, vendor, and inventory search tools for precise discovery and downstream actions.

Agent requestProduct & inventory toolsOperational action
MCP Python FastAPI Qdrant
View on GitHub

ML Project Templates

Reusable Copier templates that generate standardized repositories, development tooling, CI/CD configuration, and deployment patterns from a product name. They cut time from project kickoff to deployment by about 58%, and give teams a consistent foundation for machine learning and Artificial Intelligence product delivery.

Product nameCopier templateProduction-ready repository

Retail Chat Agent ETL

A production-grade data platform that turns raw e-commerce catalogs into multimodal, search-ready product data. Airflow orchestrates web and API ingestion, image storage, metadata processing, and synchronized text and image embeddings in Qdrant.

Catalog feedsAirflow orchestrationMultimodal vectorsProduct search
Apache Airflow Python AWS S3 PostgreSQL OpenAI CLIP BLIP Qdrant
View on GitHub

Where I've worked

Experience

Machine Learning Engineer @ Northwestern Medicine

Chicago, IL  ·  December 2024 – Present

  • Architected and deployed a high-concurrency Artificial Intelligence inference platform on Azure Kubernetes Service with NVIDIA Triton and ONNX-optimized models, sustaining sub-2-second P99 latency for real-time radiology-report analysis.
  • Built production observability for model-serving endpoints with native metrics, Prometheus, and Grafana, giving teams visibility into latency, throughput, concurrency, GPU utilization, and model health.
  • Designed a resilient LLMOps pipeline across Azure Databricks and GPU-accelerated infrastructure for daily Mixtral 8x7B batch inference, with automated retries, failure recovery, and operational alerts.
  • Led DevSecOps improvements in Azure DevOps, identifying and remediating 150+ critical vulnerabilities before production deployment and reducing failed remote CI/CD runs by 40%+.
DatabricksDockerLLMOpsMLflowMLOpsPySparkKubernetesTerraformAzure DevOps

Python Developer / Artificial Intelligence Engineer @ MyCartsOnline

Lagos, Nigeria (Contract)  ·  October 2025 – February 2026

  • Designed and deployed a multimodal search platform combining BLIP-based auto-captioning with OpenCLIP (768D) embeddings to enable high-precision text-to-image and image-to-image retrieval from a product catalog.
  • Implemented a RAG layer backed by Qdrant, improving semantic matching and boosting search precision by 40% over the baseline ChromaDB implementation through optimized vector indexing and hybrid retrieval strategies.
  • Engineered a high-throughput Airflow data ingestion pipeline that automated real-time catalog synchronization for 10K+ products at 60 items/sec.
  • Built a Model Context Protocol (MCP) server exposing inventory, product, and vendor search capabilities, enabling multi-agent systems to perform real-time lookups, supplier matching, and product discovery through a unified tool layer.
LangChainOpenCLIPBLIPRAGQdrantAirflowFastAPIMLflowGithub ActionsTerraform

Data Scientist @ Blue Lambda Technologies

Atlanta, GA  ·  May 2023 – November 2024

  • Architected and scaled end-to-end ML systems across three distinct domains (real estate, retail, finance), delivering PyTorch, XGBoost, and Scikit-Learn models to production with 95%+ uptime via AWS SageMaker for scalable batch inference and automated retraining.
  • Collaborated on the development and deployment of an internal RAG platform using LangChain and Qdrant with Gemma 3.4B, resolving up to 7,000 weekly employee queries and reducing support ticket volume by 42% with 88% first-pass accuracy.
  • Owned the data engineering backbone for 15+ concurrent models; built and maintained robust ETL pipelines using PySpark on Databricks/AWS EMR, strictly enforcing data lineage and quality gates to ensure production-grade, validated datasets.
  • Instituted proactive MLOps monitoring using Arize and MLflow to detect data and concept drift; integrated auto-alerts and rollback protocols, sustaining <5% metrics degradation across models over 18-month lifecycles.
PythonMachine LearningDockerETL/ELTSQLFastAPIMLflowGithub ActionsTerraform

Graduate Research Fellow @ University of Kentucky

Lexington, Kentucky  ·  January 2021 – May 2023

  • Implemented optimization software (AIMS, R, and Python) and prescriptive analytics on resource allocation problems for bourbon manufacturing firms, culminating in published research and improving operational efficiency by 22%.
  • Conducted rigorous statistical modeling for academic research papers, utilizing R and Python to validate complex datasets and ensure 95% confidence intervals of predictions.
  • Authored research findings based on predictive modeling techniques covering market trends for industrial hemp firms.
  • Developed strong foundations in quantitative methods, econometric analysis, and data-driven decision making directly applied to real-world agricultural economics datasets.
PythonRStatistical ModelingOptimizationEconometricsPredictive Analytics

Data Scientist @ Fiverr

Lagos, Nigeria (Remote)  ·  January 2019 – November 2020

  • Delivered custom ML solutions (Scikit-learn, XGBoost) for classification and regression across diverse client portfolios, achieving 15% average R² uplift and 22% precision gain by directly aligning model metrics to business-critical KPIs.
  • Architected a real-time incremental data ingestion system using PySpark on AWS EMR, processing over 1.5M rows per run with sub-minute latency, reducing data-to-model latency by 87% and enabling live predictive scoring.
  • Refactored legacy Jupyter notebooks into modular, PEP8-compliant packages; instituted comprehensive pytest/unittest suites (unit/integration/E2E), achieving 99% test coverage and guaranteeing audit-ready client handoffs.
  • Drove model governance and transparency by integrating SHAP values and model cards directly into production APIs, empowering clients to trust and act on predictions with verifiable confidence.
PythonXGBoostSHAPPySparkScikit-LearnSQLPandas

Content & Learning Intern @ Gidi Mobile

Victoria Island, Lagos, Nigeria  ·  January 2018 – December 2018

  • Optimized mobile learning content for a WAEC prep application serving 10,000+ students, ensuring 100% alignment with national education policy and quality standards.
  • Leveraged user feedback analysis and research to drive a 15% improvement in content engagement, providing data-backed insights for iterative platform enhancements.
  • Streamlined content delivery workflows and coordinated large-scale uploads to support organizational strategies for expanding educational access.
  • Coordinated cross-functional workflows between the research and technical teams to streamline the deployment of high-priority exam prep features.
Web ContentContent ResearchEducation Policy

Academic background

Education

Master of Science @ University of Kentucky

Lexington, Kentucky  ·  2023

  • Specialized in Hemp Economics with a focus on production optimization and price analysis.
  • Applied quantitative methods, econometric modeling and statistical analysis to real-world economic datasets in international trade and hemp industries.
  • Developed strong foundations in research methodology, optimization (linear programming), and data-driven decision making.
MicroeconomicsMacroeconomicsEconometricsStatisticsQuantitative Research

Bachelor of Science @ University of Benin

Benin-City, Nigeria  ·  2017

  • Specialized in Production Economics with a focus on technical and operational efficiency.
  • Studied microeconomics, macroeconomics, and quantitative methods applied to production systems.
  • Completed coursework in macroeconomics, microeconomics, statistics, and project planning.
MacroeconomicsMicroeconomicsStatisticsPredictive AnalyticsRegression Analysis

Let’s talk.

I’m open to Artificial Intelligence and Machine Learning opportunities, thoughtful collaborations, and building systems that solve real problems.

Email me View résumé