Experience

Warp

• Latvia
• Design Services
• 1 - 100 Employee

• Founder

  • Feb 2023 - Present

  New York City Metropolitan Area Building Warp (YC W23) – modern payroll and compliance for startups.



Rize Education

• United States
• Higher Education
• 1 - 100 Employee

• Product and Growth

  • Aug 2021 - Aug 2022

  Rize's mission is to provide a fun and riskless pathway to fulfilling employment for every learner. Working on all things Growth.



Yelp

• United States
• Technology, Information and Internet
• 700 & Above Employee

• Software Engineer, Core ML

  • Aug 2020 - Aug 2021

  San Francisco, California, United States Building Core ML infrastructure to empower Yelp-wide ML applications.

• Machine Learning Intern

  • Jun 2019 - Aug 2019

  San Francisco Bay Area Improved Yelp's photo classification service by 17% by re-writing and training the dish classification model Improved coverage of classified photos by 33%. Improved model training pipeline with better frameworks + scripts.



Massachusetts Institute of Technology

• United States
• Higher Education
• 700 & Above Employee

• Undergraduate Researcher

  • Feb 2016 - May 2016

  Cambridge, Massachusetts Working as an Undergraduate Researcher with Michael McDonald, Associate Professor of Physics at MIT, I worked to apply and optimize ASMOOTH, an adaptive smoothing algorithm by Ebeling, White and Rangarajan developed in 2006. I studied practical applications of ASMOOTH in visualizing X-Ray image data from distant massive galaxy clusters. The project involved a detailed study of the algorithm, its implementation for smoothing astronomical image data, optimizing free parameters for… Show more Working as an Undergraduate Researcher with Michael McDonald, Associate Professor of Physics at MIT, I worked to apply and optimize ASMOOTH, an adaptive smoothing algorithm by Ebeling, White and Rangarajan developed in 2006. I studied practical applications of ASMOOTH in visualizing X-Ray image data from distant massive galaxy clusters. The project involved a detailed study of the algorithm, its implementation for smoothing astronomical image data, optimizing free parameters for unambiguous visual structure and exploring mathematical methods to further improve algorithm’s output and performance. Technologies involved: Linux Environment, CIAO (X-Ray data analysis software), CSmooth, Python, Numpy and Scipy Show less