Rishabh Singh Verma

Experience

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  DRDO

  Jul 2011 - Aug 2011

  Summer Trainee

  Worked as an intern/trainee in the Network Services Division(NSD) of Defence Scientific Information & Documentation Center (DESIDOC), Defence Research and Development Organization(DRDO) - Study on Topologies of Complex and Hybrid Networks

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  Seaboltz, NSIT

  Sept 2012 - Jul 2013

  Founder and Head of Electronics and Acoustics teams

  - Led a team of 22 students; Team Seaboltz, an initiative in the field of naval research.- Was actively involved in Electronics Design, Acoustics Design, Computer Vision and Market Research- Role involved effective Team Management; tasks included sensor usage, design of Passive SONAR system using omnidirectional hydrophones, Vision Module creation- Project covered by CNN-IBN news as part of innovations happening across Netaji Subhas Institute of Technology

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  Maharshi Electronic Systems

  Dec 2012 - Jan 2013

  Winter Intern

  Autonomous Underwater Vehicle Systems Development

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  DRDO

  Jun 2013 - Aug 2013

  Summer Intern

  Worked as an intern/trainee in the Hydrophones Group of Solid State Physics Laboratory(SSPL), Defence Research and Development Organization(DRDO) - Study on Autonomous Underwater Vehicle as a sensor

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  Sapient Global Markets

  Jul 2014 - Mar 2015

  Junior Associate : Mobile Developer Java

  -Worked on a randomized algorithm for simulating Stock Exchange system based on several parameters-Worked on the transaction approval process for a Master Data Management System for trading centers in different parts of world-Introduced to technologies such as Java, J2EE, Hibernate Framework, Spring Framework, Spring MVC Framework, Apache Tomcat server management, Maven

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  Yahoo

  Jun 2016 - Sept 2016

  Technical Intern II

  As a member of Platform as a Service team in Cloud Services group :- Learnt about CI/CD model and multiple things about cloud, application deployment, build configuration and large scale distributed systems- Worked on configuration addition in servlet containers for upgrade of the internal cloud- Worked on optimization of image layering in docker to reduce build time for deployed applications in YQL- Worked on design and architecture of system for reducing pull time from docker registry for large clusters- Technologies :­ Perl, Git, Docker, Python, Jenkins Show less

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  Yahoo

  Feb 2017 - Aug 2021

  Worked in Big-data Machine Learning group at the intersection of software engineering and machine learning.- Implemented tier-based CPU compute resource allocation and eviction to handle underutilization for on-premise hosted Jupyter notebook service platform (like “Google Colaboratory” on premise)- Optimized the ML platform build release (CI/CD) process causing US-West cluster failure (build storm) via a step by step hierarchical release (from an exponential to a linear count - to a best to at most 3 times) for ML docker images’ build process in the ML-Bundle pipeline- Optimizing ML image dependency graph- Streamlined tier-based GPU compute resource allocation and eviction to handle underutilization for on-premise hosted Jupyter notebook service platform (like “Google Colaboratory” on premise)- Added fixes to internal model/feature store platform- Fixed various ML sample/starter notebooks for data scientists’ productivity Show less - Data Science track lead for Verizon Telco Marketflow project- ISP labeling using household graph for 150M unique users (90M unique households)- Improving Data quality for the projects and KPIs created across data from 2 years, long tail data included- Removing data bias from certain carriers- Data/ETL Pipelines created/managed for project- Internal paper submission : "Political Insights: the understanding of political leanings and targeting of political campaigns"- External talk : "Recommendations in the wild" Show less Working in Insights group under Data org in the following teams :1. Audience Insights2. Consumer Insights3. Politics InsightsPublications:1. Defensive Publication : “Method and System for Conducting Online Political Polling Using Machine Learning Models” IP.com, 2019 (Details under publications)Submissions:1. “Politically Sensitive: Poll without Asking”, Yahoo! (VerizonMedia) TechPulse, 20192. “Anomaly Detection in Online User Activity”, Yahoo! (VerizonMedia) TechPulse, 20193. "Quantifying content trends and approximating KPIs", Yahoo! (VerizonMedia) TechPulse, 2019Data Engineering and Science projects:1. Building and productionizing end to end big data pipeline for Consumer Insights product2. Building CI/CD pipeline for staging for Audience Insights product3. Brainstorming and Ideation process for data science features in Politics Insights product4. Maintenance and debugging production/customer issues5. Partly working on productionizing clustering pipeline6. Adding data (ETL) related features to the product7. Generating recommendations for user segments using Collaborative Filtering (In Progress) Show less Part of a selective 2 year rotational program for engineers.Currently working in Insights group as a part of the first yearly rotation.Teams (Data Org.):1. Audience Insights (AI)2. Consumer Insights (CI)3. Politics Insights (PI)Submissions:“Improvements to Audience Insights : Top Insights and Recommendations”, Yahoo! (Oath) TechPulse, 2018Projects/Experiments (check 'Projects' section for details):1. Improving Audience comparison metric (affinity) using distance/correlation measures (AI)2. Audience segment/cohort understanding and deriving key distinguishing factors using Clustering (AI) (partial)3. Anomaly detection in Counters data for proactive prevention of data indexing pipeline failure (AI)4. Audience and item group recommendation using purchase funnel modeling for better/selective segment creation using collaborative filtering/recommender system (AI) (Ideation)5. Ranking for trending content titles and topics for various content properties across the company (News, Sports, Finance etc.) (CI)6. Sentiment analysis for content based on text in articles for various content properties across the company (News, Sports, Finance etc.) (CI)7. Political bias/lean score for news content domains (PI)8. User partisan lean score calculation across political parties (PI) Show less Teams (Cloud Services, Science and Technology Org.):1. Public Cloud Platforms (PCP)2. Platform as a Service (PaaS)3. Infrastructure as a Service (IaaS)4. Yahoo Query Language (YQL)Publications:“Auto-scaling for Hybrid Cloud based Apps : Reactive, Predictive and Hybrid,” Yahoo! (Oath) TechPulse, 2017Projects (check 'Projects' section for details):1. Logging solutions for Kubernetes on AWS (PCP)2. Moving YQL tables from Sherpa (Yahoo’s distributed NoSQL key-value store) to S3/DynamoDB on AWS with data encryption using AWS KMS (YQL + PCP)3. Certificate management, mutual authentication (TLS) and service creation (YQL + PCP)4. Reactive and Predictive Auto-scaling for apps on docker container based PaaS platform (YQL + PaaS)5. Simple Node.js app for Cloud.corp (a platform for onboarding beginners at Yahoo) with extensive documentation​ (IaaS)6. Migration of legacy PHP app in production to docker container based PaaS platform (YQL + PaaS) Show less

  • Senior Research Engineer

    Feb 2021 - Aug 2021

  • Data Scientist II

    Jan 2020 - Feb 2021

  • Software Development Engineer II

    Apr 2019 - Jan 2020

  • Software Development Engineer - Engineering Associates Program

    May 2018 - Mar 2019

  • Software Engineer

    Feb 2017 - Apr 2018
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  Verizon

  Aug 2021 - Dec 2023

  Senior Software Engineer, Machine Learning

  - Worked on the LLM platform enablement and vendor evaluations (for vector stores, prompting, indexing, quantization and GPU footprint reduction) for NLP based (transcript/document summarization) Generative AI use cases- Worked on real-time models (Seldon-core), batch models, feature store and other use-cases for Verizon Business Group- Worked on Computer Vision platform proof of concept - Image DB, Image Labeling and other data prep components- Worked on the API Gateway (APIGEE), docker image release pipeline, benchmarking for pose detection (CV) models- Enabled distributed computing through Ray (for spark and DL use-cases) for various models- Worked on the end to end lifecycle of various types of ML models for Google Cloud Platform based hybrid cloud MLOps platform- Migrated ML platform components from Yahoo to Verizon and worked on their stability/optimization Show less

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  Tiger Analytics

  Feb 2024 - now

  Lead Machine Learning Engineer

  - Working on projects across ML lifecycle