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Data Science, Machine Learning & AI Engineer with a robust mathematics foundation and 18+ months of proven client delivery. Expert in the complete ML lifecycle: from data engineering & validation to model training/selection and production deployment via FastAPI/Docker/AWS with comprehensive MLOps practices. 🎯 Client Portfolio: E-commerce demand forecasting, B2B SaaS ticket triage, fintech OCR systems |
class MaxHart:
def __init__(self):
self.role = "DS/ML/AI Engineer"
self.education = "MSc AI/ML (Distinction)"
self.experience = "18+ months consulting"
self.specialties = [
"Production ML Systems",
"Computer Vision & NLP",
"MLOps & Deployment",
"Biomedical AI Research"
]
def current_focus(self):
return "Building scalable AI solutions" |
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Hybrid CNN-Transformer for Medical Imaging 🏗️ Two-Stage Architecture: 3D ResNet (256-D latent) + Transformer mapping |
End-to-End Face Recognition & Vector Search 🔍 CV Pipeline: MTCNN detection → InceptionResNet 512D embeddings |
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Multi-Model Job Recommender & LLM Assistant 🤖 AI Matching: Fine-tuned HF models + classical ML ensemble |
High-Performance Image Classification 🏆 SOTA Results: 78% top-1 accuracy on CIFAR-100 |
Machine Learning & Software Engineer • Remote
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Key Deliverables:
- 📊 Built client-facing NLP pipeline with Streamlit insights dashboard used by non-technical teams
- 🔧 Prototyped OCR (OpenCV + Tesseract) for invoice processing with REST integration
- 🚀 Integrated ML endpoints into TypeScript/Angular + Java/Spring stacks with auth & monitoring
International Education Specialist • China
- 🌍 Xi'an Jiaotong–Liverpool University (Sep 2021 - Dec 2022)
Advanced mathematics to international cohorts, revision workshops, 1:1 support - 🏫 Overseas Chinese Academy (Sep 2019 - Sep 2021)
Multi-level lesson plans, formative assessments, data-driven curriculum optimization
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University of Birmingham (Sep 2024 - Sep 2025) Core Modules:
Dissertation: Towards Generalisable Inverse Modelling for FD-DOT via a Hybrid CNN–Transformer Leadership: Organised and taught weekly maths sessions for ~30 postgraduates |
Lancaster University (Sep 2016 - Jul 2019) Foundation: Advanced mathematics, statistics, and probability theory with strong computational and analytical skills Senior Year Project: Colour quantisation using R and K-means clustering algorithm - Grade: 90%
Group Project: Time series analysis using Kruskal-Wallis test for seasonality determination |
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