Hi, I'm Daniel Akhabue
AI/ML engineer with 5+ years of industry experience designing and deploying production-grade AI systems. Currently pursuing an M.S. in Engineering AI at Carnegie Mellon University, bridging deep industry experience with formal research in embodied AI, swarm robotics, and IoT edge intelligence.
Impact Metrics
Core Expertise
About Me
Passionate about transforming complex data into intelligent solutions that drive real-world impact and business value.
My Story
With over 5 years of experience in AI/ML engineering, I've designed and deployed production-grade AI systems including real-world multi-sensor fusion architectures for autonomous physical systems.
My research lies at the intersection of autonomous systems, multi-agent orchestration, and edge intelligence. I focus on communication mesh networks and decentralized coordination protocols for multi-robot swarm systems spanning aerial, terrestrial, and aquatic platforms.
I am further interested in federated learning frameworks for collaborative model training across distributed robot nodes, and distributed Vision-Language Model (VLM) reasoning across robot networks to enable collaborative, real-time spatial awareness in complex, dynamic environments.
Education
Core Values
Innovation
Constantly exploring new technologies and methodologies
Collaboration
Believing in the power of diverse teams and knowledge sharing
Impact
Focusing on solutions that create measurable business value
Achievements
Swarm Robotics
Architectural design of communication mesh networks and decentralized coordination protocols for multi-robot swarm systems
Edge AI
Localized machine learning deployed directly on resource-constrained embedded hardware for cost-efficient inference
Federated Learning
Collaborative model training across distributed robot nodes without centralizing sensitive data
Autonomous Systems
Reinforcement learning for adaptive control and emergent coordination in multi-agent settings
Portfolio Highlights
Interactive insights into my professional journey, expertise, and achievements in data science and AI engineering
Advanced Skills Dashboard
Interactive visualizations showcasing technical expertise across programming languages, frameworks, tools, and soft skills developed over 4 years in data science and AI engineering.
Core Programming Languages
Frameworks & Libraries
PyTorch
Deep Learning & Research
TensorFlow
Production ML
Hugging Face
LLMs & Transformers
LangChain
Agentic AI Pipelines
LangGraph
Multi-Agent Orchestration
OpenCV
Computer Vision
Scikit-learn
Classical ML
ROS/ROS2
Robot Operating System
Tools & Platforms
Leadership & Soft Skills
Featured Projects
A showcase of impactful AI and data science projects that demonstrate real-world problem-solving and technical excellence.
RubiesAI — Conversational Banking AI
Nigeria's first cloud-native Agentic AI banking solution, scaling transactional capacity by 70%
Tymer — NFC & CV Workforce Management
Attendance and patrol management system combining NFC location verification with facial recognition
Pedigraph — Generative AI Analytics
NLU-powered analytics platform that auto-generates queries across databases and spreadsheets
ENVIQON — Edge-to-Cloud IoT Platform
Physical operations intelligence platform monitoring real-time environmental conditions across facility sites
Vendease Agentic AI Support
Agentic AI customer support system accelerating data access and purchase retrieval by 90%
Varsityscape AI Course Platform
Proprietary AI course-generation model reducing content development cycles by 95%
YieldSense — AI Yield Forecasting
AI-powered yield forecasting for African smallholder farmers, supporting 6 staple crops across 4 languages
Professional Journey
A timeline of my career progression, key achievements, and the technologies that have shaped my expertise in data science and AI engineering.
Senior AI/ML Engineer & Solutions Architect
Qucoon
Led the AI team in delivering generative AI solutions and cloud-native ML systems for financial and enterprise use cases.
Key Achievements:
- ▸Led the AI team to achieve AWS Generative AI competency certification, expanding business reach and client access by 90%
- ▸Architected and delivered Nigeria's first cloud-native Agentic AI banking solution, scaling transactional banking capacity by 70% and reducing customer inquiry workloads by 67%
- ▸Engineered a RAG pipeline with semantic chunking and reranking, improving context relevance scores by 85% for financial AI use cases
- ▸Optimised LLM inference pipeline (streaming, prompt compression, caching), reducing operational costs by 40% at scale
- ▸Designed and deployed AWS ML pipelines for end-to-end model training, evaluation, and serving, cutting inference latency by 40%
Agentic AI Engineer
Rubies
Pioneered serverless multi-agent conversational AI for enterprise digital banking, delivering secure and intelligent financial interactions at scale.
Key Achievements:
- ▸Pioneered a serverless, multi-agent conversational AI system enabling secure transactions, intelligent inquiries, and complaint resolution through a unified multilingual chat interface
- ▸Engineered a high-performance RAG architecture using AWS Bedrock and Lambda, achieving >99% accuracy and sub-second latency across multi-turn financial dialogues with zero infrastructure overhead
- ▸Built autonomous agentic workflows with intelligent routing, stateful context management, and event-driven core banking integration, ensuring PCI-DSS compliance and elastic scalability in production
Lead AI/ML Engineer
Vendease
Led design and development of Agentic AI systems and LLM evaluation frameworks for a food procurement platform.
Key Achievements:
- ▸Led design of Agentic AI customer support system, accelerating data access and purchase-information retrieval by 90%
- ▸Built LLM evaluation framework with 500+ test cases covering hallucination detection, tool-use accuracy, and safety
- ▸Established MLOps monitoring dashboards for real-time model drift detection
- ▸Optimised complex SQL queries, reducing report generation time from hours to minutes for downstream analytics teams
Lead Data Scientist & ML Engineer
VarsityScape
Spearheaded AI adoption strategy for a global EdTech platform, building agentic AI systems and proprietary course-generation models.
Key Achievements:
- ▸Spearheaded global AI adoption strategy, reducing content development cycles by 95%
- ▸Led development of proprietary AI course-generation model using Azure AI, reducing manual content creation by 40%
- ▸Architected and deployed Agentic AI student-class assistants, improving query resolution time by 60%
- ▸Built classification models to analyse student engagement patterns on 10K+ interaction time-series records
- ▸Designed content recommendation system using collaborative filtering and matrix factorisation
AI Community Manager
Data Scientists Network (DSN)
Mentored 50+ beginners in Data Science and AI/ML, and spearheaded institutional AI capacity expansion.
Key Achievements:
- ▸Mentored 50+ beginners in Data Science and AI/ML through structured learning programs
- ▸Spearheaded joint initiative with University of Benin to establish a Centre of AI Development
Data Visualization Engineer
WirelessNg International Limited
Designed and delivered a data analytics solution to track revenue and operational insights for a telecoms company.
Key Achievements:
- ▸Designed and developed a data analytics dashboard for tracking revenue and operational insights using Microsoft Power BI
- ▸Engineered an end-to-end data pipeline for analytics use cases using Power Query, Microsoft Excel, and Power BI
- ▸Helped the organisation manage operational costs and improve service delivery through data-driven insights
Freelance Python Developer
Self-Employed
Delivered Python-based automation and analytics solutions for clients across web scraping, QA, and data visualisation use cases.
Key Achievements:
- ▸Developed automated web scraping tools using Python to extract, clean, and structure data from multiple sources for client use cases
- ▸Built software testing automation tools to streamline QA workflows, improving testing efficiency and reliability for client projects
- ▸Designed and developed a data analytics dashboard for revenue and operational insights using Microsoft Power BI, Power Query, and Excel
M.S. Engineering Artificial Intelligence
Carnegie Mellon University
Specializing in embodied AI, swarm robotics, and IoT edge intelligence. Coursework includes Robotics: Principles & Practice; Applied Stochastic Processes; Data, Inference, and Machine Learning.
Key Achievements:
- ▸Community Researcher at Machine Learning Collective (MLC)
- ▸Co-authored poster at Deep Learning Indaba 2026 — Best Poster Award
- ▸Invited Speaker, Black in Robotics 2025
- ▸Seeking summer 2027 research/engineering internship in multi-agent systems, robotics, or edge AI
B.Eng. Computer Engineering
University of Benin
Bachelor of Engineering in Computer Engineering with focus on AI and embedded systems.
Key Achievements:
- ▸Matthew Okpebholo Foundation Scholarship — awarded to top final-year students in Edo State, Nigeria
- ▸Top 15 Global Finalist, Peter Drucker Challenge Essay Contest — Peter Drucker Society Europe, 2020
Interactive Resume
Explore my professional journey, education, certifications, and research contributions
Led the AI team in delivering generative AI solutions and cloud-native ML systems for financial and enterprise use cases.
Pioneered serverless multi-agent conversational AI for enterprise digital banking, delivering secure and intelligent financial interactions at scale.
Led design and development of Agentic AI systems and LLM evaluation frameworks for a food procurement platform.
Spearheaded AI adoption strategy for a global EdTech platform, building agentic AI systems and proprietary course-generation models.
Mentored 50+ beginners in Data Science and AI/ML, and spearheaded institutional AI capacity expansion.
Designed and delivered a data analytics solution to track revenue and operational insights for a telecoms company.
Delivered Python-based automation and analytics solutions for clients across web scraping, QA, and data visualisation use cases.
Key Achievements
Quantifiable impact and measurable results that demonstrate expertise in data science, machine learning, and AI engineering across diverse projects and teams.
Model Accuracy Improved
Enhanced ML model performance across multiple projects
Processing Time Reduced
Optimized data pipelines and model inference speed
ML Models Deployed
Production-ready models serving real users
Data Points Processed
Massive datasets analyzed and transformed
Cross-functional Projects Led
Successfully managed diverse technical teams
Professional Recognition
Deep Learning Indaba 2026, RIAD Poster Session
Zaka x Zindi Africa, Team Synergy — Dec 2023
6+ international AI & robotics conferences
Federated Learning on real edge hardware — Deep Learning Indaba 2026
Awarded to top final-year students in Edo State, Nigeria
Peter Drucker Challenge Essay Contest — Peter Drucker Society Europe, 2020
Let's Build Something Amazing
Ready to transform your data into actionable insights? Let's discuss your next AI project.
Send a Message
Get in Touch
danakhabue@gmail.com
GitHub
github.com/Apprentice-doa
Location
Pittsburgh, PA (CMU)
Availability Status
Open for new projects and collaborations. Typical response time: 24 hours.
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