Kristine Petrosyan
Senior AI MLOps Engineer at Clarvos
Austin, Texas, United States
Summary
👤
Senior🎓
Top SchoolKristine Petrosyan is a Senior AI MLOps Engineer with a decade of experience building and operationalizing scalable ML systems that tie technical rigor to business strategy. Holding an MS in Artificial Intelligence and an MBA, she blends deep engineering skills with product and stakeholder awareness to deliver reproducible, monitored models in production. Her background spans end-to-end MLOps—model development, automated deployment, and real-time monitoring—plus hands-on work in computer vision for TinyML and spatial analytics using xarray-spatial. An active open-source contributor, she has extended spatial classification methods and built Scrapy spiders to broaden real-world data collection for projects like alltheplaces. Based in Austin, she brings a pragmatic focus on measurable business outcomes and a knack for converting messy geospatial and sensor data into dependable ML pipelines.
10 years of coding experience
8 years of employment as a software developer
Master's Degree Artificial Intelligence, Master's Degree Artificial Intelligence at The University of Texas at AustinData Science Immersive, Data Science Immersive at Flatiron SchoolMaster’s Degree MBA, Master’s Degree MBA at American University of ArmeniaBachelor’s Degree Computer Science, Bachelor’s Degree Computer Science at State Engineering University of Armenia
English, Armenian, Russian, Spanish, French
Github Skills (19)
json-parser10
json10
python10
scikit10
xray10
jsonp10
webscraping10
scrapy10
spider10
parsing10
html-parsing10
xa10
scikit-learn10
data-extraction10
numba10
Programming languages (4)
Github contributions (5)
makepath/xarray-spatial
Apr 2020 - Jun 2020
Raster-based Spatial Analytics for Python
Role in this project:
Data Scientist
Data ScientistContributions:7 commits, 5 PRs, 73 pushes in 2 months
Contributions summary:Kristine contributed significantly to the xarray-spatial project by implementing and testing spatial classification methods, including natural breaks and equal interval classifications. They developed new functionality within the `classify.py` module and added corresponding tests in `test_classify.py`. The user's commits show a focus on integrating machine learning techniques (K-means) and adapting existing spatial analysis tools within the xarray and Numba framework.
raster-analysisrasterioanalyticspythonspatial-analysis
alltheplaces/alltheplaces
Nov 2017 - Dec 2017
A set of spiders and scrapers to extract location information from places that post their location on the internet.
Role in this project:Back-end Developer
Back-end DeveloperContributions:35 commits, 23 PRs, 34 pushes in 23 days
Contributions summary:Kristine primarily contributed to the development of web scraping spiders using the Scrapy framework. Their work involved creating and modifying spiders to extract location data from various websites, including CVS, Marshalls, Panera Bread, and others. They focused on parsing HTML and JSON responses, extracting relevant information such as addresses, hours of operation, and geographical coordinates. The user's contributions aimed to expand the repository's capability to gather location data from a wider range of sources.
pythonscrapyspiderscraperslocation
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.