Algis Kasniunas
About Algis Kasniunas
Algis Kasniunas is a Senior Applied Machine Learning Engineer at Snorkel AI, where he focuses on developing innovative AI solutions and enhancing data labeling efficiency. With a background in aerospace engineering and advanced analytics, he has held various roles in the field, including positions at Slalom and NASA.
Work at Snorkel AI
Algis Kasniunas currently serves as a Senior Applied Machine Learning Engineer at Snorkel AI, a position he has held since 2022 in Chicago, Illinois. In this role, he engages in collaborative team efforts to create impactful AI products that challenge industry norms. He has contributed to the development of machine learning models that enhance data labeling efficiency and participated in projects aimed at transforming industry practices through innovative AI solutions.
Previous Experience at Slalom
Prior to his current role, Algis worked at Slalom in various capacities. He served as a Principal in Advanced Analytics from 2020 to 2021, and as a Solution Architect in Advanced Analytics for one month in 2020. Additionally, he was a Consultant in Advanced Analytics from 2018 to 2020. His experience at Slalom provided him with a strong background in advanced analytics, which informs his current machine learning work.
Background in Aerospace Engineering
Algis Kasniunas has a background in aerospace engineering, having worked as a Systems Engineer in the Space Systems Group at Sierra Nevada Corporation from 2017 to 2018. He also held positions at NASA as a Life Support Systems Engineer and Integration & Systems Engineer for one month each in 2016. This experience in aerospace engineering, combined with his machine learning expertise, provides him with a unique interdisciplinary perspective.
Education and Expertise
Algis holds a Master of Science (MS) in Aerospace Engineering from the University of Colorado Boulder, which he completed from 2014 to 2017. He also earned a Bachelor of Science (BS) in Chemistry from Butler University from 2008 to 2012. Additionally, he is pursuing a Certificate in Artificial Intelligence from Stanford University School of Engineering, expected to be completed in 2024. His educational background supports his expertise in both aerospace engineering and machine learning.