At spAItial, my work turns frontier world models into shipped products: app.spaitial.ai, the developer API, model-serving infrastructure, eval tooling, demos, and agent-ready integrations for LLM skills, MCPs, and Claude plugins. Before frontier AI, I spent six years shipping user-facing products (B2B and B2C) and co-created Danfo.js (5k+ GitHub stars, featured by the TensorFlow team) and other open-source tools used by thousands of developers.
<EXPERIENCE/>
{> Member of Technical Staff (Product Engineering)
spAItialBuilding spAItial's frontier world-model platform across app.spaitial.ai, the developer API, agent-ready integrations, demos, eval tooling, and customer-facing product work. Launched the product and API from scratch on scalable infrastructure, including programmatic access, LLM skills, MCPs, Claude plugins, and deployment paths for inference endpoints. Helped build large-scale data sourcing, scraping, and training-data pipelines. Also built Eval tooling, launch campaigns, and product/partnership loops with users and partners.
{> Senior Full Stack Software Engineer
KallikorBuilt AI-powered simulation products for turning real-world operations into digital twins, giving enterprise teams a way to test decisions in software before changing physical systems.
{> Senior Full Stack Software Engineer
Nossa DataEarly engineering hire who helped take Nossa Data's ESG reporting and data-management platform from MVP to production, shaping the architecture, data workflows, and core customer-facing features.
{> Engineering Lead
PhilanthroLabLed development of the Social Safety Net, a search engine for social services powered by a machine-learning-ready knowledge graph that matched people in need with relevant resources.
{> Software Engineer
DatopianCore contributor to PortalJS (2k+ GitHub stars), an open-source framework for building rich data portals. Extended the framework, improved backend integrations including CKAN, and helped teams publish more usable data products.
{> Machine Learning Engineer
Data Science NigeriaWorked on applied machine-learning and analytics projects across the full data loop: collection, exploration, transformation, modeling, evaluation, and business-facing insight.
<SKILLS/>
> Here are my technical skills and areas of expertise:
> Technical Stack
> Domain Expertise
<SELECTED PROJECTS/>
A browser-based 3D Gaussian-splat segmentation playground powered by spAItial worlds. Select and isolate objects inside reconstructed 3D scenes, rendered in real time in the browser.
A browser-based demo where a humanoid bot learns to navigate and fetch inside worlds generated by the SpAItial API. Reinforcement learning runs client-side in a web worker, with PlayCanvas rendering, Rapier physics, generated splats, collision meshes, and pretrained policies.
One interface to chat with your Google, Apple & Outlook calendars. Bring all your calendars (Google, Apple, Outlook) into a single view. Chat to schedule meetings, manage events, and organize your life through natural conversation. Available in TestFlight.
2D Animation Editor - Create simple 2D animations with ease from your browser, no need to install any software. This intuitive browser-based editor lets you create frame-by-frame animations, add keyframes, and export your work in various formats. Perfect for creating animated GIFs, short videos, and simple motion graphics.
<RESEARCH PAPERS/>
> Optimizing Health Facilities Allocation for COVID-19 Management Using Social Vulnerability Index and Spatial Data Analysis
This study recognises that building new health centers would be slow and expensive in preparation for the pandemic and as such uses social vulnerability index, demographic and environmental statistics to propose suitable existing centers that needs to be re-equipped.
Read Paper >> DataSist: A Python-based library for easy data analysis, visualization and modeling
This paper presents a new python-based library, DataSist, which offers high level, intuitive and easy to use functions, and methods that helps data scientists/analyst to quickly analyze, mine and visualize big data sets
Read Paper >> Predicting Bank Loan Default with Extreme Gradient Boosting
This paper provides an effective basis for loan credit approval in order to identify risky customers from a large number of loan applications using predictive modeling.
Read Paper ><TALKS/>
<BLOGS/>
> Building an Intelligent Calendar Assistant
Exploring the development of an AI-powered calendar app that transforms how users interact with their schedules through natural language and multi-calendar integration.
Read Article >> How to put machine learning models into production
An opinion piece curating best guide in putting machine learning models in production
Read Article >> How to Serve Machine Learning Models with TensorFlow Serving and Docker
Learn how efficiently serve machine learning models with Tensorflow serving
Read Article >> Deep Dive into ML Models in Production Using Tensorflow Extended (TFX) and Kubeflow
An end-to-end tutorial that shows you how to deploy, scale and monitor deep learning models with Tensorflow Extended and Kubeflow on GCP
Read Article ><CONNECT/>
> echo "Let's connect!. Here's how you can reach me:"
> echo "I'm always open to interesting conversations and collaborations!"