Berlin, Berlin, Germany
Head of AI/ML (10 years) with a strong background in Machine Learning and MLOps across various domains including information retrieval (Search, Recommendations, RAG-systems & ChatBots), NLP, and Customer Analytics. Brand new: AI Agents! I specialize in guiding cross-functional teams of ML Engineers, Software Engineers, etc. to build scalable, event-driven ML solutions with a focus on robust MLOps practices using Python/PySpark and cloud platforms like AWS, GCP, etc. - (GCP Certified ML Engineer) Currently, at HeyJobs, I have been fortunate to initiate and lead multiple complex ML projects (Search, RecSys, NLP and AI Agent) that that have significantly outperformed previous benchmarks and generated substantial business value. Additionally, I also designed and lead the implementation of a new MLOps and monitoring framework that has been embraced across all Data Science teams within the company. Additionally, I love learning the latest advancements in the ML space, always exploring new ideas to push boundaries and improve outcomes. I’m also dedicated to mentoring and sharing knowledge, focused on building systems that drive innovation and business outcome.
As an ML Engineering Manager at HeyJobs, I am responsible to drive the development and optimization of ML-driven Search and Recommendation systems that enhance user experience and user-job Matching on our platform while building robust MLOps frameworks. I lead a cross-functional team of ML Engineers, Data Engineers, and Software Engineers, focusing on implementing state-of-the-art machine learning systems, advanced MLOps practices, and NLP techniques leveraging various AWS and other services to deliver high-impact solutions aligned with business goals. - Led the successful implementation and tuning/optimization of a new Search engine for job searches. This reduced considerable costs, improved key business KPIs, and enabled the addition of advanced features like Learning to Rank (LTR) and personalized search experiences. - Proposed and led the development and deployment of a state-of-the-art job recommendation system using Vector DB, which personalizes job matches across million of new job listings with very low latency. This project significantly increased business KPIs, doubling the performance compared to previous systems. - Introduced new tooling and led the development of the first general MLOps template at HeyJobs, which streamlined MLOps implementations across teams, reducing the deployment timeline from months to just days, ensuring faster and more reliable model deployment. - Managing and supporting development of NLP techniques,integration of LLMs to enhanced data extraction and driving innovation. - Mentor and guide ML Engineers, Analysts and Software Engineers within and beyond my team. - Support multiple data science projects beyond my team, contributing to initiatives in Marketing, Sales, and other areas.
Blogging, sharing real-world AI insights :)
- Developed and deployed scalable microservices on Google Cloud Platform (GCP) using FastAPI and Cloud SQL, implementing RESTful APIs for efficient communication. - Built an MLOps framework in GCP for automating the retraining of Transformer-based NLP models using TensorFlow, ensuring continuous model improvement. - Created and deployed a full-stack, ML-powered web application that allows document uploads (PDF/Word) for text manipulations like chapter separation and question-answer generation, leveraging Transformer-based NLP models in TensorFlow. - Worked on Python-based microservices for user tracking and ML-driven behavior analysis, using advanced NLP techniques (regex 😉) to improve the accuracy of cookie-free tracking data.
- Led the development and deployment of an NLP-based classification model in Flask framework, automating commentary generation and email notifications for the Liquidity Management team, enhancing operational efficiency. - Implemented MLOps practices using on-premise infrastructure and internal cloud solutions, orchestrating model deployment and monitoring, ensuring scalability, reliability, and continuous integration of machine learning solutions. - Automated complex financial calculations for the Product Control department using R, and developed an RShiny dashboard for interactive statistical visualization. - Developed a recommendation system prototype for internal finance tools, improving the personalization of data insights and decision-making support.
- Developed an email classification using NLP techniques and simple neural networks, improving categorization accuracy. - Designed and implemented an RNN-based sequence-to-sequence model in TensorFlow for an in-house chatbot PoC. - Created automation test cases with Selenium, streamlining testing processes and reducing deployment time.