The ML Engineer bridges ML development and operational deployment, leveraging expertise in algorithms and MLOps practices. Responsibilities include model development, pipeline setup, performance monitoring, workflow optimization, and collaboration for innovation. Seamless integration of ML solutions into scalable systems enhances the organization's data-driven insights.
- Python / R / Matlab / C / C++ / Node.js / React.js / JavaScript
- Machine Learning / Deep Learning / Computer Vision / Natural Language Processing / Pattern Recognition
- PyTorch / Tensorflow / Keras / OpenCV
- Deepfake Detection / Athlete Action Detection (MeidiaPipe) / MTG Card Detection
- RAG / LLM / Langchain / Langgrpah
- terraform / Azure
- Django / Flask
- Data Science / Big Data / ETL / Data Visualization / Data Engineering / Data Integration / Data Modeling / Data Mining / Data Quality / Data Manipulation
- SQL / MongoDB
- Cloudflare R2
- Blockchain Ecosystem (Airdrop Strategies, White trading, Sybil Analysis)
- Mathematics / Statistics
- Trading Strategies
- 🔭 I’m currently working on programming and software development
- 🤝 I’m interested in collaborating with entrepreneurs on new venture creation & development
- 🌱 I’m currently learning Deep Reinforcement Learning
- 💬 Ask me about anything related to tech & business; happy to help!
- 📚 When I am free, I watch Premier League & La Liga and Listen to Music