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AI Engineer with 4+ years in End-to-End ML Pipelines & Multi-Agent AI
ML Infrastructure and Systems Engineer with hands-on experience designing, building, and deploying end-to-end machine learning pipelines — from data ingestion and experiment tracking through model packaging, production rollout, and observability. Proficient in Python, PyTorch, NumPy, Docker, FastAPI, and distributed ML systems. Proven builder of autonomous multi-agent AI architectures (LangGraph, FAISS, ChromaDB, Pinecone) and scalable backend execution pipelines. Brings first-principles engineering discipline to ML reproducibility, configuration management, CI/CD for ML, and operational readiness. Eager to apply these capabilities to General Motors' Embodied AI / Offboard Perception team, delivering ground-truth–quality world estimates that accelerate safe autonomous vehicle development.
Unknown
Bachelor of Science · Computer Science
N/A – June 30, 2026
Independent AI Systems Engineering
Senior ML Infrastructure & AI Systems Engineer
January 1, 2022 – Present
India
Lagos Tourism Data Platform
June 4, 2026 – Present
Interactive data journalism platform (Chart.js, ReportLab PDF export) demonstrating production deployment and observability for public-facing analytics.
IGR Per Capita Visualization (Statisense)
June 4, 2026 – Present
Interactive Nigerian state-level data visualization with real-time filtering, plain-language explainers, and public API data integration.
Generative Anime System
June 4, 2026 – Present
GAN-based animation using PyTorch, OpenPose, MediaPipe — custom text encoder/tokenizer trained on real movement data, built from scratch without framework abstractions.
Autonomous OS-Control Agent
June 4, 2026 – Present
Five-layer agent architecture (LangGraph, AutoGen, CrewAI, Docker sandboxing, MCP tool schemas, HITL gates) — production-grade ML orchestration system.
ML Specialization (In Progress)
Deeplearning.ai
June 1, 2026 – Present
Computer Vision Engineer Certification
Society for AI
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, including personal projects like 'Autonomous OS-Control Agent' and 'Generative Anime System', showcases a strong passion for AI and continuous learning beyond formal employment. Their freelance experience as a 'Senior ML Infrastructure & AI Systems Engineer' indicates self-direction, initiative, and adaptability. The explicit mention of applying capabilities to a specific team (General Motors' Embodied AI / Offboard Perception) demonstrates targeted interest and alignment with advanced AI research and development environments.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through complex project implementations and a first-principles approach to ML. Their experience with production-grade systems and CI/CD practices suggests a high degree of operational maturity and attention to detail. The emphasis on documentation and clear separation of concerns indicates good collaboration potential and maintainability focus.