Deep Learning Engineer

● Implemented the ML-powered DSS (Decision Support System) for a US-based transportation company

○ To predict the demand on stop/trip/route level of the SamTrans buses running in San Mateo county.

○ To predict the bus occupancies of the SamTrans with highly skewed and highly variations in the data.

Technology Stack: Python, Scikit learn, Xgboost.

Machine Learning Engineer

● Worked on a project to solve a business problem where a skill map (an ordered collection of skills) needs to be generated for a particular user in order to achieve a role in the IT industry.

○ Built a deep learning model to detect the sentences containing one or more

skill keywords.

Technology stack: Python, Prodigy, SpaCy, NLTK.

○ Built a NER-based deep learning model to automatically extract hard and soft

skill keywords from the job descriptions.

Technology Stack: Python, Prodigy, SpaCy, NLTK.

● Single-handedly built an MVP where the objective was to read the characters in the Indian Digital Electric Meter. We have built a model using an object detection

algorithm YOLO v3 with Transfer Learning. Technology Stack: Python, TensorFlow, Keras, PyTorch, OpenCV.

● Worked on data scraping using Python to scrape the job descriptions for a particular job role from a job site in order to automate the data collection process.

Technology Stack: Python, Selenium, Beautiful Soup