Makarand Parigi's Resume

Stripe — Machine Learning Engineer, Advanced Attacks

Mar 2024 – Present

Building and deploying machine learning models to detect card testing fraud, helping protect merchants from fraudulent transactions.
Developing pattern recognition systems to identify suspicious transaction patterns that indicate fraud or card testing attempts.

Nextdoor — Machine Learning Engineer, Vitality ML

May 2023 – Nov 2023

Led the development and deployment of an ML model to evaluate posts and comments for potential community guideline violations. This model served as a critical metric for monitoring violative content on the platform.
Proactively addressed data quality challenges; proposed and executed plan to use GPT to enrich the training dataset, significantly improving model performance (+0.12 PR-AUC).

Twitter — Machine Learning Engineer II, Trust & Safety

Aug 2021 – Feb 2023

Led team of 3 developers to improve Abuse Detection model by incorporating media features, resulting in a 10% increase in model precision and my promotion to mid-level engineer.
Conducted A/B online experiments, resulting in a 15% increase in remediation volume and addition of 2 tweet languages to our scope.
Migrated tweet report ranking model to Google Cloud's Dataflow, leading to a 63% increase in report action rate and a decrease in model training time by approximately 90%.
Independently created an internal web tool to run our abuse detection model with sample inputs.
Simplified training data generation with BigQuery and refactored TensorFlow model training code to reduce engineering time required for training new models.

University of Michigan Radiology — Research Assistant, Deep Learning for MRI Reconstruction

June 2020 – Dec 2020

Created novel deep learning architecture in PyTorch to reconstruct undersampled brain MRI acquisitions, achieving baseline performance with 50% fewer parameters.
Adapting the U-net for Multi-coil MRI Reconstruction published as an extended abstract at the International Society for Magnetic Resonance in Medicine (ISMRM) 2021.
Presented at Neuromatch 3.0, a neuroscience conference.

University of Michigan Computer Science — Teaching Assistant

Jan 2018 – Apr 2021 · Programming Languages Theory, OOP and Data Structures in C++, Intro to Programming

Led development of instructional materials for 1000+ students per semester.
Hosted exam review sessions, taught discussion sections, delivered lectures, and assisted students in office hours.

Internships

Twitter — SWE Intern, JVM Team

Summer 2019

Developed Neuroevolution program to evolve a neural network to use as a heuristic for Method Inlining, a compiler optimization. Implemented for GraalVM's Java compiler.
Presented at CGO 2020's Graal Workshop: Experimenting with Neuroevolution for Graal Inlining Heuristics

Amazon — SWE Intern, Growth Engagement at Amazon Music

Summer 2018

Designed and implemented AWS architecture so marketing campaigns could send push notifications into the web application. Used new browser technologies (Service Workers, Push API).

Skills

Technologies: Deep Learning Frameworks (TensorFlow/Keras, PyTorch), Stream and Batch Processing Systems (Spark, Beam), Query Engines (BigQuery, Databricks), ML Orchestration (Flyte, Kubeflow, Airflow)

Resume

Experience

Internships

Skills

Education