Food QA Retrieval System
View →Production-style Q&A API using Retrieval-Augmented Generation with document chunking and vector indexing.
ML Engineer · Data Engineer
Stuti Nayak
Building production ML systems, NLP pipelines, and LLM-powered applications integrated with real-world data pipelines and cloud infrastructure.
The Hague, Netherlands Open to roles NL / EU
What I Build
- Machine Learning Systems NLP classification pipelines (BERT / RoBERTa)
- LLM Applications Retrieval-Augmented Generation systems
- Data Infrastructure Streaming pipelines and ML deployment systems
Selected Systems
Filter by skill
NLP Classification Pipeline
View →BERT/BERTopic multi-label classification; RoBERTa sentiment analysis pipeline deployed on AWS.
Streaming Data Pipeline
IoT simulation pipeline using Kafka ingestion, processing layer, and ML analytics on Google Cloud.
Churn Prediction
View →End-to-end ML project predicting customer churn for a telecom company with EDA and model deployment.
Experience
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Data Engineer
Built Kafka-based IoT simulation pipeline and secure streaming architecture with data governance.
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Data Scientist, Knownwell
NLP classification using BERT / BERTopic; RoBERTa sentiment analysis; deployed on AWS and GCP.
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Data Scientist, Rate.nl
wav2vec 2.0 audio analysis; MLFlow MLOps pipeline; Google Cloud deployment.
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Researcher, Clinical Data Science, Maastricht University
Vantage federated learning infrastructure; semantic data modeling.
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Research Assistant, Institute of Data Science, Maastricht University
Deep learning models for biomedical metadata; CNN achieved 83% accuracy.
Toolkit
- ML / AI
- PythonPyTorchTransformersLangChainRAGMLFlowScikit-learn
- Data
- KafkaSQLPandasFastAPIGradio
- Cloud
- AWSGCP
Education
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M.Sc. Data Science in Decision Making
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B.Tech. Information and Communication Technology
Outside Work
- Anime fan: always on the lookout for the next great series
- Fitness enthusiast: staying active and pushing limits
- Coffee geek: passionate about good brews and the ritual behind them
- Horror movie lover: the scarier, the better