Santosh Mohan
About Santosh Mohan
Santosh Mohan is a Staff Machine Learning Engineer at Normal Computing, having transitioned to this role in January 2024. He has a diverse background in machine learning and software engineering, with previous positions at notable companies including Google, Amazon Web Services, and Salesforce.
Current Role at Normal Computing
Santosh Mohan serves as a Staff Machine Learning Engineer at Normal Computing. He began this role in January 2024 and has been contributing to the company's machine learning initiatives. His expertise in AI and machine learning is instrumental in developing innovative solutions within the organization.
Previous Experience at Major Tech Companies
Prior to his current position, Santosh Mohan worked at several prominent technology companies. He was a Machine Learning Engineer at Apple for one month in 2019. He also held the role of Software Development Engineer at Amazon Web Services (AWS) from 2016 to 2017. Additionally, he worked as a Software Engineer at Google from 2020 to 2023, gaining valuable experience in software development and machine learning applications.
Educational Background in Computer Science and AI
Santosh Mohan earned a Bachelor of Science degree in Computer Science and Applied Mathematics from the University of Michigan. He furthered his education by obtaining a Master of Science degree in Artificial Intelligence from Stanford University. This academic foundation supports his expertise in machine learning and data science.
Internship Experience at the United Nations
In 2016, Santosh Mohan completed a three-month internship as a Data Scientist Intern at the United Nations in Rome, Italy. This experience provided him with insights into data analysis and its applications in international organizations.
Experience in AI/ML Startups
Santosh Mohan has experience working with pre-seed and seed stage AI and machine learning application and infrastructure companies. This background enhances his understanding of the startup ecosystem and the challenges faced by emerging technology firms.