Smit Kiri
About Smit Kiri
Smit Kiri is a Senior Machine Learning Engineer currently working at Klaviyo in Boston, Massachusetts. He has a background in machine learning and data science, with experience in various roles including teaching assistant and intern, and holds a Master's degree in Data Science from Northeastern University.
Work at Klaviyo
Smit Kiri currently serves as a Senior Machine Learning Engineer at Klaviyo, a position held since 2023. Previously, he worked as a Machine Learning Engineer at the same company from 2022 to 2023. During his tenure, he designed and implemented a real-time model serving framework that supports hundreds of thousands of models. He also led the team's preparation for Black Friday/Cyber Monday, managing a significant increase in customer traffic. Additionally, he enhanced the Jenkins CI pipeline, resulting in improved speed and reduced size, and performed advanced Terraform state manipulations to clarify resource ownership across multiple teams.
Education and Expertise
Smit Kiri holds a Master of Science in Data Science from Northeastern University, where he studied from 2019 to 2021. Prior to this, he earned a Bachelor of Engineering in Computer Engineering from Gujarat Technological University (GTU) from 2015 to 2019. His educational background has equipped him with a strong foundation in data science and machine learning, which he applies in his professional roles.
Background
Smit Kiri has a diverse background in machine learning and data science. He began his career as a Machine Learning Intern at SculptSoft in 2018, followed by a Machine Learning Engineer Co-op position at Reboot Rx in 2021. He also served as a Graduate Teaching Assistant at Khoury College of Computer Sciences in 2020 and 2021, where he contributed to the academic development of students in computer sciences.
Achievements
Throughout his career, Smit Kiri has achieved significant milestones in his roles. At Klaviyo, he led critical initiatives during peak traffic periods and enhanced operational processes, such as the Jenkins CI pipeline. His contributions have had a measurable impact on the efficiency and scalability of machine learning operations within the organization.