Sergey Zelvenskiy

Lead ML Engineer

San Mateo, California, United States18 yrs 10 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in Machine Learning and NLP.
Proven track record in fraud detection systems.
Strong background in building scalable eCommerce platforms.

Stackforce AI infers this person is a Machine Learning Engineer with expertise in SaaS and eCommerce solutions.

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Skills

Core Skills

Machine LearningNatural Language ProcessingProduct ManagementSoftware Development

Other Skills

ScalaAkkaApache SparkApache StormApache Kafkaxgboostdata qualityexperiment trackingtime-series anomaly detectionSparkno-code systemsautomated financial advisorJavaeCommerceJavaScript

About

Techno optimist

Experience

18 yrs 10 mos

Total Experience

3 yrs 1 mo

Average Tenure

7 yrs 3 mos

Current Experience

Uber

Staff Software Engineer

Feb 2019 – Present · 7 yrs 3 mos · Sunnyvale, California, United States

Builder of Risk Entity Watch 👀: https://www.uber.com/blog/risk-entity-watch/
Builder of RADAR 📡: https://eng.uber.com/project-radar-intelligent-early-fraud-detection/
Contributor to Uber Michelangelo: https://eng.uber.com/michelangelo-machine-learning-platform/

ScalaAkkaNatural Language ProcessingMachine LearningApache SparkApache Storm+1

Walmart labs

Lead Machine Learning Engineer

Jan 2018 – Feb 2019 · 1 yr 1 mo · San Francisco Bay Area

Drastically improved feature engineering system including data quality controls, fast onboarding, and experiment tracking capabilities.
Supported the implementation of the text classification models using NLP/convolutional networks
Supported the implementation of search ranking using xgboost- lambdamart
Rebuilt catalog indexing pipeline bringing 10x optimization of resource utilization, consistency testing, linear scalability, and performance improvements.
Designed and implemented the processes for data quality and search results validation

Natural Language ProcessingMachine Learningxgboostdata qualityexperiment tracking

Thinair

Lead Machine Learning Engneer

Apr 2016 – Jan 2018 · 1 yr 9 mos · Palo Alto, CA

Built the AI for detecting malicious user activities using custom-designed time-series anomaly detection algorithms. Scaled to handle 4 billion events per day.
Build Spark-based framework for hosting streaming apps featuring the following capabilities:
Breaking change for stateful streaming apps
Realtime reconfiguration without restart
Time series functions for GroupBy aggregations
Time-series Forward fill/Backward fill
Distributed unique counts
Built the simulation system for the user behavior using Monte-Carlo sampling methods implemented using on Akka
Developed AI chatbot capable of producing advanced data reports based on natural language commands.

Machine Learningtime-series anomaly detectionSparkAkka

Zignal labs

NLP Data Pipeline Engneer

Sep 2014 – Apr 2016 · 1 yr 7 mos · San Francisco Bay Area

Real-time data stream analysis and NLP using Apache Spark, Scala, Akka, Lucene, Elastic Search, Apache Storm
Custom NLP models, which go beyond sentiment analysis

Natural Language ProcessingApache SparkScalaAkka

Forusall

Co-founder & CTO

Sep 2012 – Sep 2014 · 2 yrs · San Francisco Bay Area

Built no-code system for managing "Dave" - a proprietary automated financial advisor.
This technology platform:
delivered an order of magnitude improvement in terms of employee engagement in financial transactions over the industry baseline.
helped to raise tens of millions of dollars in funding
grow the company to billions in assets under management.

no-code systemsautomated financial advisorProduct Management