Machine Learning Engineer2020 - PRESENTAAQUA
Technologies: Scikit-learn, Python, Go, Elasticsearch, AWS DynamoDB, Neo4j, Natural Language Processing (NLP)
- Built and deployed multiple personalization ML pipelines to power the main user feed for the app. The pipelines were built using Python, Kafka, AWS S3, scikit-learn, and NLTK and deployed to AWS.
- Designed, architected, and built an end-to-end search solution using Python and Elasticsearch. The analytics pipeline that drives data-driven decisions and better search results' relevance ranking was built using Kafka, Amazon Pinpoint, and AWS S3.
- Designed, architected, and built an end-to-end autocomplete solution using Python and Elasticsearch. The analytics pipeline that drives data-driven decisions and relevance ranking of search results was built using Kafka, Amazon Pinpoint, and AWS S3.
Technical Reviewer2020 - 2020Packt Publishing
Technologies: Technical Writing, Natural Language Processing (NLP), PyTorch
- Collaborated with the team to test out all code samples and make sure it was easy for users to replicate the projects from the book. The code consisted of neural networks built in PyTorch and various other pre-processing utilities in NLTK.
- Worked with the editing team to review all the book chapters and make necessary corrections, technical and otherwise.
- Suggested various improvements in terms of the book content.
Machine Learning Engineer2020 - 2020Knowt
Technologies: Python, SpaCy, PyTorch, Deep Learning
- Developed a deep neural net with multiple heads using ELMo embeddings to identify phrases that could be used to generate quizzes and achieve other downstream tasks. The model was built using Python, PyTorch, and Flair and deployed to AWS.
- Developed a pipeline using spaCy and Python to extract triplets from textual data, build relations using them, and represent it in the form of a knowledge graph.
- Led initiatives to build a dataset to train models based on implicit user feedback.
Data Scientist2018 - 2018Cookt
Technologies: NLTK, SpaCy, Python, AWS
- Developed a heuristic algorithm using named-entity recognition (NER), spaCy, and the natural language toolkit (NLTK) to identify cooking ingredients from recipe instruction data.
- Created an algorithm to use identified ingredients to generate optimal cooking instructions to reduce friction for end-users.
- Bundled the model into an API and worked with the in-house tech team to integrate it into the entire stack.