# Evan Chrisinger > Senior Software Engineer at Remitly Location: Seattle, Washington, United States Profile: https://flows.cv/evanchrisinger I write robust software in complex domains & guide the technical growth of the orgs I work in with strong data, ML ops & backend experience. Have guided platform & product domains in companies from 10-4000, seen growth to IPO, and created technical roadmaps that scaled teams. Strong believer that complicated technology can be simple, expressive and facilitate growth with thoughtful design. Former student at Claremont McKenna, while studying Computer Science at Harvey Mudd. Outside of work, I'm an athlete. I spend a lot of time surfing, skiing, climbing & playing soccer. ## Work Experience ### Senior Software Engineer @ Remitly Jan 2020 – Present | Seattle, Washington, United States Experienced in scaling platforms, projects & infra for hyper growth. In the past I've created instrumental portions of our Fraud prevention infra, from data & feature engineering to higher level business domains. Currently building out the Trust Platform to support a multi-product line future. ### Software Engineer @ Transfix Jan 2018 – Jan 2020 | Greater New York City Area ML Ops: Application, data, and some infrastructure engineering. Productionized machine learning models for scalable API use, developing a pricing rules engine, and trying to construct relationships between their outputs. Product Engineering: Built out features around carrier tracking, automated communication (customer notifications), and other features for the company's internal load board. Languages: Python, Ruby, Postgres, Ruby (Rails), Java, Node (a little) Tools: Lambda, EC2, ECS, SQS, SNS, Elasticache (Redis), RDS, ECS, Redshift, Snowflake, Redis, Airflow, Terraform, CircleCI, etc. ### HMC Clinic Team Software Developer @ Lawrence Livermore National Laboratory Jan 2017 – Jan 2018 | Claremont, CA Applied and evaluated physical simulation regressors to data in a distributed-memory parallel context (LLNL's supercomputing infrastructure). Researched current learning methods on imbalanced class distributions and used those to composed locally trained classifiers for a node's training subset. Reduced those models into a superset classification algorithm while retaining performant regression versus our baseline comparison. In layman's terms, find an untuned model, train an instance on each compute node's portion of the data, combine all nodes' trained models in some fashion (the hard part). Choose models based on research & intuition, tune, and integrate the resulting model into existing experiments. Tech used: Python, scikit, MPI ### Software Engineering Intern @ Voodoo Manufacturing Jan 2017 – Jan 2017 | Greater New York City Area Voodoo Manufacturing was a Y-Combinator company focused on creating a fully automated factory of 3D printers, to enabling rapid prototyping and low-scale manufacturing. In my internship, I designed the first iteration of an automated job assigner to manage factory load. I also built out parts of the client-facing website and internal tools. Learned a lot about choreographed event driven architectures. Tech: Go, Rails, React/Node, Kafka ### HIV Research Intern @ Fred Hutch Jan 2016 – Jan 2016 | Greater Seattle Area HIV research underneath Nicole Frahm and Bryan Simons. ## Education ### Bachelor's degree in Computer Science Claremont McKenna College ### Bachelor's degree in Computer Science Harvey Mudd College ### UPrep Seattle ## Contact & Social - LinkedIn: https://linkedin.com/in/echrisinger --- Source: https://flows.cv/evanchrisinger JSON Resume: https://flows.cv/evanchrisinger/resume.json Last updated: 2026-03-31