Co-founder and CTO2018 - 2019Tint.ai
Technologies: Python, AWS, Docker, Machine Learning, Terraform, Elasticsearch, API
- Created from scratch a fully automated machine learning platform for evaluating the impact of external data sources on various customers' machine learning problems and serving them in production.
- Developed a data pipeline for ingesting CSV datasets, enriching them through REST APIs from partners, feature engineering, and automated machine learning (AutoML) training.
- Created a REST API in Python (Flask) running on AWS Lambda with an API Gateway for inference.
- Developed a GraphQL API in Node.js (Apollo) for serving the web application.
- Developed a web application in React.
- Developed an elasticsearch cluster for performant search on millions of records.
- Oversaw the advanced monitoring and alerting infrastructure using AWS CloudWatch, Elasticsearch, and PagerDuty for monitoring all components. Achieved an uptime of 99.99%.
- Created infrastructure as Code with Terraform for the entire architecture on AWS (RDS, ECS, EC2, S3, Athena, SecretsManager).
- Implemented authentication and identity management with Auth0 for all the microservices.
Senior Software Engineer2017 - 2018
Technologies: Java, Python, Unix, Kubernetes, Android, API
- Led the technical efforts for launching Google Pay (mobile NFC payments) in new markets (Japan, Korea) with radically different technologies.
- Designed and implemented NFC-F payment support in the Google Pay Android app in partnership with phone carriers (NTT Docomo).
- Integrated Google Pay back end with payment providers and major banks in Japan, in Java.
- Worked closely with Lotte (biggest retail group in South Korea) to design and implement the integration of their rewards program in Google Pay.
- Implemented support for store credit cards (credit cards which are only usable in one store, such as Macy's card, Gap card) in Google Pay US.
Engineering Team Lead2015 - 2017Remind
Technologies: Java, Go, Python, AWS, Android
- Led the development of Remind's android application. Remind is the leading education messaging platform in the US, with over 50 million active users. The app is #1 of both the App and Play Store in September every year.
- Set up and managed DevOps processes for both the Android and iOS application using AWS and CircleCI.
- Designed and overviewed the migration of Remind's API from REST to GraphQL to better serve web and mobile clients.
- Developed messaging and notification back-end microservices in Go.
Senior Software Engineer2012 - 2015
Technologies: Python, Ruby, Java, Android, AWS
- Worked as a back-end engineer on the SlideShare team.
- Re-designed and implemented the file upload back end allowing various formats of presentations (PDF, PPT) to be uploaded and served on the SlideShare platform. Tech stack: Ruby on Rails, Python, PostgreSQL, RabbitMQ.
- Started and led the development of the LinkedIn SlideShare Android app, in a team of four engineers. Received 4.3+ stars reviews and over 20 million installations. Appeared in Google's official Best Apps of 2014. Tech stack: Java, Android, DevOps.
Senior Software Engineer2011 - 2012Motorola Mobility
Technologies: Java API
- Worked for the file-sharing startup Zecter in a team of five and acquired by Motorola Mobility after a few months.
- Participated in the development of the MotoCast application (streaming and synchronization of media content in a private Cloud), used daily by over 600,000 unique users representing a1600% growth over nine months.
- Designed and implemented a peer-to-peer synchronization API in Java.
- Developed the streaming server app in Java, in a team with a team of three.
Software Engineer2009 - 2011CLS Group
Technologies: Java, Python, API, SQL
- Designed and developed an end-to-end solution allowing any Android-powered device to communicate over the Iridium satellite constellation network, in a team of two.
- Worked on the REST Api and Android Application in Java.
R&D Intern2009 - 2009Thales Alenia Space
- Designed and developed a new GPS navigation map-matching algorithm adapted to a road-charging context, based on the Viterbi algorithm.
- Developed several data-formatting and testing scripts in Python.
- Analyzed the performance of this algorithm against other existing GPS-based navigation algorithms.