Tejas Dharamsi

Tejas Dharamsi is a highly accomplished professional in the field of Machine Learning and Software Engineering. Here's a comprehensive overview of his career and background:

Professional Experience

Tejas has an impressive career trajectory in the tech industry:

Sr Staff Software Engineer, Machine Learning at LinkedIn (July 2023 - Present)1
ML Engineer | Tech Lead at Twitter (April 2021 - May 2023)1
Machine Learning Engineer at Twitter (September 2019 - April 2021)1
Machine Learning Engineer at Trifacta (January 2018 - September 2019)1
Data Science Research Intern (IBM Social Good Fellow) at IBM (September 2017 - December 2017)1
Software Engineer Intern, Machine Learning at Trifacta (May 2017 - August 2017)1
Summer Research Intern at Carnegie Mellon University (May 2015 - August 2015)1
Google Summer of Code participant (February 2014 - November 2014)1

Education

Tejas has a strong educational background:

Master's Degree from Columbia University in the City of New York (2016 - 2017)1
Bachelor's Degree from People's Education Society Institute of Technology (2012 - 2016)1
Attended Rosary High School (1998 - 2012)1

Skills and Expertise

Tejas possesses a wide range of technical skills, including:

Machine Learning, Deep Learning, Distributed Systems, Data Warehouse, Large Scale Systems, Algorithms, Apache Spark, Big Data Analytics, C++, Java, Python, JavaScript, Natural Language Processing, and TensorFlow1 2

Personal Interests

Outside of his professional life, Tejas enjoys:

Playing chess
Urban hiking
Participating in Hackathons

Career Highlights

Tejas has worked on significant projects at Twitter, including the Video Product, RecSys & Explore Page, and Events1
He has experience in AI for Social Good and Data Driven Application Development
Tejas has received several honors and awards, including being a finalist in the ATOS IT Challenge 2014 and receiving a scholarship from the Sports Authority of India1

Tejas Dharamsi's career demonstrates a strong focus on Machine Learning and its applications in large-scale systems, particularly in social media and data-driven environments. His transition from Twitter to LinkedIn as a Sr Staff Software Engineer in Machine Learning indicates his continued growth and expertise in the field.1