Victoria Salvati is a software engineer with 11 years of experience specializing in robot autonomy, SLAM, and probabilistic robotics, currently building next-generation airborne robots and eVTOL-powered precision agriculture systems. She has a strong track record of turning prototypes into production-grade, cost-effective systems—most recently re-architecting a Python path-planning prototype into a modular solution for autonomous crop-spraying drones. At iRobot she shipped fleet-scale SLAM and mapping improvements, saved ~$80k in cloud costs through map-size controls, and boosted ML model precision from 83% to 93% by crafting novel features and tooling. Fluent in C++/C and Python and experienced with ROS, OpenCV, PCL, TensorFlow, and GraphQL/React integrations, she pairs deep algorithmic knowledge with pragmatic engineering and clear documentation. A former TA and graduate researcher in robotics, she also enjoys filling process and knowledge gaps to elevate team standards and accelerate root-cause debugging.
10 years of coding experience
10 years of employment as a software developer
UMass Lowell
High School, Classics, 3.86 GPA, High School, Classics, 3.86 GPA at Haverhill High School
Contributions:1 PR, 82 pushes, 17 branches in 1 year 11 months
data-analysispythonscienceaggregationdata-science
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