Anina Hitt
About Anina Hitt
Anina Hitt is a Backend Software Engineer at percipient.ai, where she has worked since 2021. She holds a Bachelor's degree in Computer Science from Brown University and has experience in various roles, including performance engineering and software development internships.
Work at Percipient
Anina Hitt has been employed at Percipient.ai as a Backend Software Engineer since 2021. In this role, she has contributed to significant enhancements in the video analysis component by re-architecting a batch approach to a horizontally scalable streaming method, achieving a 150x speed-up on a critical release-blocking bottleneck. Additionally, she implemented dynamic filters by developing a dynamic layout for search results. Anina has also conducted workshops and mentored developers on backend development and Django REST basics, showcasing her commitment to knowledge sharing within the team.
Education and Expertise
Anina Hitt earned her Bachelor's degree in Computer Science from Brown University, where she studied from 2016 to 2020. During her time at Brown, she also served as a Teacher Assistant for CSCI 60 and as a Data Science Intern, gaining practical experience in teaching and data analysis. Prior to her university education, she completed her high school diploma at Summit Rainier from 2012 to 2016. Anina's educational background provides her with a solid foundation in computer science principles and practices.
Previous Work Experience
Before joining Percipient.ai, Anina Hitt worked at Splunk as a Performance Engineer from 2020 to 2021. She also held positions at Brown University, including a Data Science Intern and a Backend Software Engineering Intern. Additionally, she gained experience as a Product Intern at CareerVillage.org and as a Software Development Intern at Ethos. Her diverse work history has equipped her with a range of skills in software development, performance engineering, and product management.
Technical Contributions
Anina Hitt has made notable contributions to various technical projects throughout her career. At Percipient.ai, she implemented prioritized indexing to enhance the efficiency of comparing machine learning embeddings, significantly reducing runtime and enabling previously infeasible features. She also created a multi-intelligence processing service that condenses and monitors multiple types of sensor data using PostgreSQL and Flask endpoints. Her work demonstrates her ability to tackle complex technical challenges and improve system performance.