Twitter, Machine Learning Engineer II, July 2021 – Present
Team: ML Pipelines, Cortex
• Design, build, and maintain ML pipeline infrastructure for teams operating at scale by leveraging industry leading technologies, including TensorFlow Extended (TFX), Kubeflow, Apache Beam, Dataflow, BigQuery, Apache Airflow, Jupyter Notebook, and Weights & Biases.
• Scope and implement features that measurably reduce the time it takes ML practitioners to deploy their models to production.
• Streamline onboarding to Twitter’s modern ML stack and scale customer support by documenting best practices, case studies, and training materials. Invited to participate in Twitter’s TechDocs customer advisory board.
• Enable cross-functional stakeholders to achieve impactful business outcomes by learning about their domain specific problems and advising them on how to effectively use our tooling.
• Reduce maintenance costs by driving upgrades and deprecations and by maintaining an internal library of shared utilities that reduce copy/pasted boilerplate code. Received and was nominated for internal awards in recognition of my stewardship and tact when leading a month-long migration that resulted in a 11% reduction of the ML platform group’s GPU operations cost.
• Contribute to the open source projects we depend on by implementing usability improvements, reporting bugs, making feature requests, and providing helpful context on issues. Became a core member of the TFX Addons special interest group in October, 2022.
Twitter, Software Engineer I, Jan 2020 – July 2021
Team: ML Pipelines, Cortex
• Evaluated ML workflow orchestration frameworks according to how well they facilitated rapid experimentation, their ease of use and production readiness, and the feasibility of integrating them with Twitter’s standard ML stack. Contributed to my team’s report on our findings and recommendation to adopt TensorFlow Extended (TFX).
• Prototyped features that enabled performant ingestion of data stored in proprietary formats into TFX pipelines using Python, Java, Apache Beam, Dataflow, Apache Avro, and BigQuery. Wrote accepted RFCs that drove alignment and influenced the roadmaps of our partner teams.
• Member of Twitter’s Python Working Group: reviewed changes to third-party Python dependencies in Twitter’s monorepo, provided feedback on internal Python tooling, and provided community support to other Python developers.
Twitter, Software Engineering Intern, May 2019 – Aug 2019
Team: ML Platform Tools, Cortex
Prototyped a solution to streamline the new user experience of ML Workflows, an internal tool designed to automate, schedule, and share machine learning pipelines. Backend development using Python.
Twitter, Software Engineering Intern, May 2018 – Aug 2018
Team: Ad Quality, Revenue Experience
The City University of New York, Hunter College
B.A. in Computer Science, Jan 2020
Honors & Awards: Phi Beta Kappa
Selected Coursework: Open Source Software Development, Language Technology, Supervised Research: Computational Models of Syntax Acquisition, Supervised Research: Using Kernel Methods and Model Selection to Predict Preterm Birth
Columbia University, Columbia College
B.A. in American Studies, May 2015
Honors & Awards: John W. Kluge Scholar, Dean’s List (Spring 2014, Fall 2014, Spring 2015)
Selected Coursework: Computing in Context – Digital Humanities, Languages of America, Advanced Italian I, Intermediate Latin I, Advanced Workshop in Translation, Rapid Reading and Translation in Italian
ML libraries and frameworks: TensorFlow Extended (TFX), Kubeflow, Apache Beam, GCP Dataflow, Apache Airflow, GCP BigQuery, Jupyter Notebook, Weights & Biases
TensorFlow Extended Contributor, 2020 – Present
Association for Computational Linguistics Member, 2020 – Present
Association for Computing Machinery Member, 2016 – Present
GitHub Campus Expert, 2019
Rewriting the Code Fellow, 2019
Hunter College ACM Student Chapter Vice President, 2019
Italian (professional, B2/C1)
Swedish (professional, B1/B2)
Nyanja (limited, A2/B1)
Latin (limited, A2/B1)