💻 Machine Learning Engineer | Data Scientist | Data Engineer
🎓 M. Sc. Data Engineering & Analytics (TU München) | Alumni of TU Darmstadt
📍 Munich, Germany
I’m passionate about building scalable AI systems that bridge the gap between research and production.
Over the past years, I’ve worked on recommendation engines, chatbots, real-time analytics pipelines, and trend detection systems – always with the goal of turning data into impactful, user-facing products.
Currently I’m working on:
- 🧠 Developing & deploying personalized recommendation systems
- 🤖 Building chatbots and NLP pipelines to automate support & marketing workflows
- 🔄 Designing CI/CD pipelines for ML models with automated retraining & monitoring
- 📊 Delivering production-ready datasets and analytics to support decision-making
- ⚡ Optimizing ML for real-time, large-scale production use
Languages: Python, SQL, Java, Scala, JavaScript, TypeScript, Bash
ML/AI Frameworks: PyTorch, TensorFlow, scikit-learn, Hugging Face, LangChain, LangGraph, spaCy, OpenCV
Data & Databases: PostgreSQL, MongoDB, BigQuery, DynamoDB, Supabase, Qdrant, FAISS
Tools & Platforms: Apache Airflow, Docker, Kubernetes, Kubeflow, Terraform, AWS, Google Analytics, Git
- 💍 vow.ing – a published wedding planning project bringing tech into event organization
- 📈 Balanced News – Built a global dynamic news crawler that detects negative news and enriches it with positive, fact-based counterpoints to balance sentiment
- 📧 Email: lukas.weigand@web.de
⭐️ I’m always open to collaboration on AI/ML, data engineering, and scalable system design projects.