# Timothy Gillis > Senior Software Engineer @ Circle Location: New York, New York, United States Profile: https://flows.cv/timothygillis Computer science graduate of Northeastern University with over 5 years of full time software engineering experience, developing in large existing codebases as well as building products from the ground up, integrations with third party services, and working with serverless pipelines in AWS. US/Brazil dual citizen. ## Work Experience ### Senior Software Engineer @ Circle Jan 2026 – Present | New York, New York, United States ### Software Engineer II @ Circle Jan 2024 – Jan 2026 | New York, New York, United States ### Software Engineer II @ LinkSquares Jan 2023 – Jan 2023 | Boston, Massachusetts, United States - Built API Gateway and corresponding infrastructure to access private VPC resources using a custom Lambda authorizer, integrating with a 3rd party authorization platform to support shift from monolith to microservices architecture. - Worked on all portions of tech stack to help build and deliver proof of concept (POC) and minimum viable product (MVP) of new product, Prioritize, from ground up, provisioning infrastructure with Terraform, building APIs in Rails, and front end components in React. - Actively participate in product discussions, planning, cross-team initiatives, and mentorship for new engineers. ### Software Engineer I @ LinkSquares Jan 2021 – Jan 2023 | Boston, Massachusetts, United States - Played integral part in overhauling document text extraction pipeline (Smart OCR) into a serverless architecture, accelerating processing time from hours/days to less than an hour per batch, significantly lowering costs by improving accuracy and reducing the need for human review or manual extraction. - Modified user document upload paths across the products to automatically integrate with the new pipeline, significantly reducing manual text extraction and manual runs of the pipeline. - Closely collaborated with the data science team to reach alignment on the Smart OCR pipeline's data output, specifically what types of data are extracted, the data format, and data storage ### Software Engineer @ Alignable Jan 2020 – Jan 2021 | Boston, Massachusetts, United States - Built high concurrency APIs in the Elixir framework, Phoenix, for personalizing marketing emails in large scale batches with the latest user data. - Implemented a deterrence system to block spammers on the platform, including foreign and VPN IP and spam keyword detection on user generated content across the site, in Rails. - Developed an email analytics tracking mechanism to improve deliverability and identify root causes for spam filtering using DynamoDB, integrating with an automated ETL pipeline in Python. - Led development and became technical point of contact for several third-party integrations to enable improved email marketing, rapid frontend A/B testing, and data compliance. ### Software Engineering Co-op @ Alignable Jan 2019 – Jan 2019 | Boston, MA - Revamped automated community newsletter generation and frontend email design using Rails, Haml, and Liquid email templating, helping lead to an approximate three times increase in monthly newsletter sponsorship revenue. - Worked closely with team members to spec, estimate development time, and implement critical features contributing to all levels of the tech stack, including robust test coverage and extensive tracking for A/B testing. ### Technical Co-op: Human Language Technology Group @ MIT Lincoln Laboratory Jan 2018 – Jan 2018 | Lexington, MA - Leveraged generative adversarial networks (GANs) and the CelebA dataset to identify facial recognition performance gaps between clean and “disguised” faces (e.g. glasses, hair color, facial hair changes), and proposed a data augmentation procedure to close said performance gaps, working daily with TensorFlow and PyTorch. - Developed an unbiased evaluation protocol for facial attribute translation models on the CelebA dataset, measuring attribute editing and preservation accuracy along with image quality preservation, which solves the problem of using cherry-picked qualitative results for comparison. ### Student Technical Assistant: Human Language Technology Group @ MIT Lincoln Laboratory Jan 2017 – Jan 2018 | Lexington, MA - Built end to end machine learning pipelines in Python to get high-quality baseline results for various datasets, in preparation for an automated system using similar datasets, as part of DARPA's Data-Driven Discovery of Models program (https://www.darpa.mil/program/data-driven-discovery-of-models). - Worked with several data science libraries including Scikit-learn, Caffe, TensorFlow, Torch, etc. ### Undergraduate Research Assistant @ Northeastern University SMILE Lab Jan 2016 – Jan 2018 | Boston, MA - Helped build the largest kinship image dataset to date Families in the Wild (FIW), consisting of over 11,000 family photos that span 1,000 unique families to promote computer vision research in kinship related problems. (see https://web.northeastern.edu/smilelab/fiw/) - Developed Java tool as part of a semi-supervised labeling pipeline to further extend Families in the Wild in a more efficient and automated manner, reducing manual labor by ~93%. - Coauthored journal extension to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) Special Issue: The Computational Face (https://ieeexplore.ieee.org/document/8337841). - Worked with fellow co-chairs to organize the first large-scale kinship recognition data competition and workshop RFIW 2017 in conjunction with ACM-Multimedia 2017, along with RFIW 2018 in conjunction with FG 2018 - Delegated tasks to fellow undergrads, ensuring individual and team goals were met, i.e., images satisfied requirements, no overlap in families or photos, and diversity (in terms of families) was obtained. ### Software Development Co-op @ Tamr Jan 2017 – Jan 2018 | Cambridge, MA - Automated manual performance, scale and full-stack regression tests in Java, testing core functionality and reducing human labor by at least three days per quality assurance engineer for each sprint. - Led development of an admin dashboard Flask app in Python to communicate with and manage multi-node, distributed product deployments on Apache Mesos/Marathon managed clusters. - Collaborated with development, QA and PM to develop strong end-to-end test cases, meeting strict deadlines in a fast-paced, Agile environment. ## Education ### Bachelor of Science (B.S.) in Computer Science Northeastern University ## Contact & Social - LinkedIn: https://linkedin.com/in/timothy-gillis --- Source: https://flows.cv/timothygillis JSON Resume: https://flows.cv/timothygillis/resume.json Last updated: 2026-03-30