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Jalil Bouziane

@jalilbouziane

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Mobile & AI engineer building data-driven health-tech applications.

Poland

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What I'm looking for

I seek roles building AI-driven mobile health applications where I can apply Flutter, ML, and backend skills in a collaborative, impact-focused team with opportunities to work on clinical-grade products and scalable cloud integrations.

I am a mobile and AI engineer specializing in Flutter, backend development, and applied machine learning, with a background in biotechnology. I design and build data-intensive health-tech applications that integrate real-time data, cloud services, and AI models to deliver user-centric solutions—from AI-powered genomic interpretation to ECG arrhythmia classification.

My work includes full-stack mobile apps (Flutter frontends, Python/FastAPI backends), RAG pipelines using large language models, and high-accuracy deep learning models (>99% for arrhythmia classification). I prioritize clean design, clinician-friendly interfaces, and robust backend systems that support secure authentication, data management, and payment processing for production-ready apps.

Experience

Work history, roles, and key accomplishments

Full-stack Mobile Engineer

VarSight

Developed VarSight, an AI-powered genomic interpretation app combining Flutter frontend and Python/FastAPI backend that aggregates public bioinformatics APIs and uses a LLM-based RAG pipeline to generate actionable variant summaries.

Flutter fastAPI Python LLMs)NCBI APIs GWAS Catalog Bioinformatics

Mobile & AI Engineer

Independent / Freelance

Built full-stack mobile and AI solutions including a genomic interpretation app (Flutter + FastAPI) with RAG pipeline and an ECG arrhythmia classifier achieving >99% accuracy, delivering production-ready apps for health-tech and e‑commerce.

Flutter Dart Python fastAPI TensorFlow PyTorch Supabase Firebase

Mobile Developer

Stride & Style

Built a cross-platform e-commerce mobile app with Firebase/Supabase backend, implementing authentication, product catalog, order tracking and Stripe payments to enable a complete storefront experience.

Flutter Firebase Supabase Stripe Firestore Authentication Payments

Machine Learning Engineer

ArrhyDetect

Designed and implemented a deep learning ECG arrhythmia classifier with an offline Python GUI and customizable clinical database, achieving >99% classification accuracy for automated diagnosis support.

Deep Learning Python TensorFlow PyTorch Signal Processing Clinical Data Management

Mobile Developer

AlhulumAlSaeed

Developed an e-learning mobile platform with admin dashboard, multilingual support, dark/light themes, push notifications and media-rich course workflows integrated with Supabase backend.

Flutter Supabase Backend Push Notifications