Filip is a Senior Data Scientist & ML Engineer who has worked on large-scale problems at Amazon and built NLP models as a research associate at University of Zagreb. Filip's main interests include ML and NLP, with an emphasis on building text classification models.
Delivering data warehouse and ETL solutions as part of an Agile team using advanced ML techniques to improve performance and processes.
Helping build and improve infrastructure, application, and performance development and ensuring tight security including data encryption, security groups, and environment scanning.
Ensuring high-quality deliverables and implementing DevOps and security best practices in fast-paced environments.
Developed an LLM-based solution to determine which scientific articles are related to user-inputted free-text criteria.
Evaluated the LLM solution performance and demonstrated metrics proving considerable improvement over the previously implemented solution.
Worked with ML engineers to deploy solutions and define an optimal architecture for applying the LLM solution.
Machine LearningPythonNatural Language Processing (NLP)
Language Models
Text Classification
Unsupervised Learning
LangChain
Amazon Web Services (AWS)
GitGPT
Text Generation
Large Language Models (LLMs)
BJS
Data Science Engineer
2022 - 2022
Remote
Developed prototype product recommenders showing customer purchasing patterns.
Built simple AWS Lambda functions to conduct an ETL workflow.
Worked with PySpark on large sets of data (>100GB of historical purchases).
Contributed to developing a scalable time-series database solution in Java and C++, which served around 1 million requests/second.
Served as the team scrum master and product owner.
Designed and implemented a network correlation engine microservice to handle networking events from the entire Amazon network (patent award https://patents.justia.com/inventor/filip-boltuzic).