David Adeyemi
Verified Expert in Engineering
DevOps Engineer and Developer
Fort Worth, TX, United States
Toptal member since May 9, 2025
David is a DevOps engineer with about six years of proven success in designing, building, and managing resilient, highly available, and cost-optimized cloud-based solutions. He has extensive experience in Kubernetes, infrastructure as code (IaC), CI/CD pipelines, and MLOps. A lifelong learner dedicated to staying ahead of evolving technologies, David has improved deployment efficiency and optimized performance using cutting-edge tools such as Terraform, Ansible, and Argo CD.
Portfolio
Experience
- DevOps - 5 years
- Ansible - 5 years
- Python - 5 years
- Argo CD - 5 years
- Azure - 5 years
- Machine Learning Operations (MLOps) - 5 years
- Machine Learning - 5 years
- Terraform - 5 years
Availability
Preferred Environment
MacOS
The most amazing...
...thing I've done involved creating videos using IBM technology covering a range of DevOps and MLOps topics.
Work Experience
Cloud and MLOps Engineer
IBM
- Established IaC practices within the data science group using Kubernetes as the foundation for scalable, cloud native infrastructure.
- Designed and maintained a CI/CD pipeline for a cloud native tool used by the managerial team, achieving 60% time savings through integrating Travis CI and Docker.
- Enhanced ETL pipelines using Tekton to improve the acquisition of data utilized by the data analytics teams, speeding up data ingestion and processing.
- Developed MLOps pipelines for deploying engineered feedback LLMs using Kubeflow and Argo CD, eliminating eight hours of monthly downtime for model deployment and management.
- Delivered monthly monitoring reports to executives and managerial teams, detailing updates, improvements, and key insights across five deployed ML models, enhancing transparency and decision-making.
- Automated routine data science tasks by developing and organizing a runbook of Python and Bash scripts, streamlining workflows and minimizing manual intervention.
- Created and integrated Kubernetes into the infrastructure stack, managing various Kubernetes objects like ReplicaSets, deployments, ConfigMaps, and secrets to ensure the scalability and reliability of machine learning model deployments.
- Developed LLMs based on BERT, DistilBERT, and proprietary IBM Granite foundation models as text classification and question answering solutions.
- Supported LLMs in deployment using model automation and observability using MLFlow.
- Developed automated deployments for MLOps pipelines using Terraform and Ansible, ensuring reproducibility and consistency across development, staging, and production environments.
Cloud Engineer
All Axis Machining
- Supported the merger of two internal systems into one cohesive enterprise resource planning (ERP) following the acquisition of another entity.
- Consulted with cross-functional leaders to gather requirements and translate business needs into technology solutions.
- Wrote IaC using Terraform to manage AWS resources like EC2, S3, VPC, Route53, EKS, and IAM.
- Participated in release meetings with technology stakeholders to identify and mitigate potential risks.
- Automated AWS image creation using CloudFormation templates.
- Created Terraform modules for consistent infrastructure provisioning.
- Developed one-click Jenkins pipelines for platform deployment, integrating Terraform, Kubernetes, and Helm.
- Automated deployment, scaling, and application management by developing Kubernetes clusters and Terraform modules.
- Wrote YAML manifests for creating pods, deployments, services, and ConfigMaps, as well as stateful and daemon sets.
- Created Docker containers for Java Spring Boot, Node.js, Python, and .NET applications.
Experience
IBM Technology Influencer
https://youtu.be/p-kAqxuJNik?si=VyozVt6wxdhNXe8LEducation
Master's Degree in Computer Engineering
University of North Texas - Denton, Texas, USA
Bachelor's Degree in Computer Engineering
University of North Texas - Denton, Texas, USA
Certifications
Terraform Associate
HashiCorp
Skills
Tools
Terraform, Ansible, Amazon Virtual Private Cloud (VPC), Travis CI, Jenkins
Languages
Python, JavaScript
Paradigms
DevOps
Platforms
Azure, MacOS, Amazon EC2, Jupyter Notebook, Docker
Storage
Amazon S3 (AWS S3)
Other
Machine Learning Operations (MLOps), Argo CD, Machine Learning, Software Development, Computer Engineering, Amazon Route 53, Robotics, Robotics Product Manager, Large Language Models (LLMs), AIOps, GitOps
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