06/26/2023 updated
AN
100 % available
Full Stack Software Engineer
Melbourne, Australia
Germany
Master’s in NLP at Carnegie Mellon UniversityHTMLJava (Programming Language)JavaScriptArtificial IntelligenceLisp (Programming Language)Amazon Web ServicesBash ShellGoogle BigQueryC++ (Programming Language)Cascading Style Sheets (CSS)ClojureComputer NetworksData ProcessingDjangoElasticsearch
Github, SDN, development environment, Git, Google, Artificial Intelligence, data-processing, Spark, Google Scholar, GREP, Scala, C++, Python, Java, Go, Rust, Ruby, Javascript, Common Lisp, Clojure, Haskell, Mathematica, Matlab, IDL, bash scripting, HTML, CSS, SVG, LESS, Sass, JSON, Protobuf, gRPC, Hosted production websites, Heroku, Digital Ocean, Amazon Web Services (AWS), NixOps, Docker, Ruby on Rails, Django, NodeJS, Play framework, Jetty, MongoDB, SQLite, MySQL, PostgreSQL, Elasticsearch, React, OpenGL, GLUT, pygame, Open Dynamics Engine, Used Hadoop, Pig, BigQuery, Flume, machine learning, data processing, GLUT's
Languages
EnglishNative speaker
Project history
* Released various features involving the entire stack, including integrations with 3P services such as Sumsub and AppsFlyer
* Maintained/improved existing soundex system for OFAC SDN compliance to below 5% false positive rate prior to manual review
* Standardized development environment via Dockerization, enabling new hires to onboard with a single command after Git setup
* Maintained/improved existing soundex system for OFAC SDN compliance to below 5% false positive rate prior to manual review
* Standardized development environment via Dockerization, enabling new hires to onboard with a single command after Git setup
* Drove Duo metrics improvements from initial identification of cross-stack opportunities to implementation and final verification
* Biggest cumulative wins include -10% in ring latency, +3.1% in call connection rates, verified extensively by A/B testing
* Implemented major migrations for the Duo client and a major rewrite of the notifications targeting pipeline that ran 500% faster
* Added Gaussian and post-aggregation partition selection, and "distinct per key" counts, to the internal differential privacy library
* Biggest cumulative wins include -10% in ring latency, +3.1% in call connection rates, verified extensively by A/B testing
* Implemented major migrations for the Duo client and a major rewrite of the notifications targeting pipeline that ran 500% faster
* Added Gaussian and post-aggregation partition selection, and "distinct per key" counts, to the internal differential privacy library
* Optimized and simplified the Semantic Scholar (S2) data-processing Spark pipeline to run in 1 hour instead of 9 hours
* Improved S2's search relevance from an NDCG 1 of 0.68 to 0.82, and a final Kendall's tau of 0.67 between S2 and Google Scholar
* Integrated new neuroscience-related features into existing computer-science only search experience
* Improved S2's search relevance from an NDCG 1 of 0.68 to 0.82, and a final Kendall's tau of 0.67 between S2 and Google Scholar
* Integrated new neuroscience-related features into existing computer-science only search experience