Nextdoor is a company building a community, neighborhood by neighborhood. It takes on almost an impossible challenge of bringing together people of different backgrounds, diverse cultures, with different mindsets, opinions, views and creating an environment where everyone is welcomed and heard. I am proud to be part of this very humane project. My work mainly focuses on notification infrastructure of Nextdoor to keep members updated and engaged.

Consensual is the future of relating between humans, a platform making dealing with day-to-day agreements manageable. It helps to create, negotiate and track the agreements in an easy way. Together with my partner we developed an effective flow as a proof of concept, a prototype website (desktop, mobile + Cordova-powered app) running on Meteor / Angular / Mongo stack and are working on attracting investments.

When I joined Linkedin Learning it was facing a challenge of merging courses from Lynda.com with its native course database to provide an extended base of online knowledge to users of both services with an improved experience by new recommendations, engagement emails and enriched supporting data associated with the courses (like social proof of course’s popularity). I worked with the full stack of Linkedin Learning from offline processes of building recommendations to frontend functionality being involved closely with Lynda engineers, Linkedin Learning data science team and collaborating with surrounding eco-system of Linkedin services (including propagating functionality of Linkedin Learning to the main Linkedin pages).

I’m a member of the Product Security Team. Our team's goal is to protect the privacy of our members' data, guarantee the safety of outgoing links on the site, prevent scraping and any form of abuse, etc. Projects I worked on include: 2-step authentication, protection from address book import abuse, protection of email lookup in partners API, safe browsing for Mobile platform, real-time protection from scraping, contacts verification and maintenance of current security infrastructure at Linkedin. All projects had a strong requirement for performing in a multi-datacenter environment, being robust and receiving huge traffic. For example, the anti-scraping service processes over 7k messages/s per server.

While working as a backend engineer I also contributed to the team's professional growth. I participated in the initiative to improve unit test coverage of our products, supported introduction of agile, lead training of other team members for the services I’m responsible for. My last initiative was promoting of usage of Scala inside our team and now I’m working on the first Scala front-end for internal security purposes.

Technologies: Java/Scala, Play, Oracle, Couchbase, Voldemort, Kafka, Hive

I lead the development of Yandex.Rabota (http://rabota.yandex.ru), Russia's largest vertical job search engine aggregator, in a team of 3 developers.

Some figures: ~1mln entities (2.5Gb data), 16 machines, 2 services: 140requests/sec peak with 99% latency <140ms; 60 req/sec peak with 99% latency <50ms. A single search query involves entity recognition in the query text, execution, snippet generation, faceted aggregation etc.

Technologies: Java, C++, MySQL, BDB, proprietary search server.