Garima Singh
About Garima Singh
Garima Singh is a Senior Machine Learning Engineer with a background in neuroscience and computer science. She has worked at various technology companies, including Rokt, Spotify, and SparkCognition, and is dedicated to leveraging technology for positive societal impact.
Current Role at Rokt
Garima Singh serves as a Senior Machine Learning Engineer at Rokt, a position she has held since 2024. Her role involves applying her expertise in machine learning to develop advanced solutions within the company. She works on-site in the New York City Metropolitan Area, contributing to Rokt's initiatives in enhancing customer engagement through technology.
Previous Experience in Machine Learning
Prior to her current role, Garima Singh worked at several notable companies in machine learning positions. She was a Machine Learning Engineer II at Spotify from 2022 to 2023, and before that, she served in a similar capacity at SparkCognition from 2020 to 2022. Her experience includes designing and productionizing machine learning models, showcasing her ability to work effectively in Agile teams.
Education and Expertise
Garima Singh holds a Bachelor of Science degree in Computer Science and Neuroscience from Yale University, where she studied from 2016 to 2020. This educational background provides her with a strong foundation in both technology and neuroscience, enhancing her capabilities in machine learning and artificial intelligence.
Background in Technology and Education Initiatives
Garima Singh has a history of involvement in educational initiatives, particularly with Girls Who Code. She served as an Alumni Liaison from 2015 to 2016 and as a Teaching Assistant in 2017. Her commitment to making a difference through technology is evident in her efforts to support and inspire the next generation of women in tech.
Internship Experience
Garima Singh gained valuable experience through internships at IBM, where she worked as a Cognitive Software Developer Intern in 2019 and as a Cognitive Developer Intern in 2018. These roles allowed her to apply her academic knowledge in practical settings, contributing to her development as a machine learning professional.