Abhishek Gupta

Engineering Leader

2020

I lead Product Engineering for the Facebook Marketplace Tab that includes Feed, Search, Messaging, Products Details, Trust and Infrastructure. We serve 100M+ daily active users and 1.3B+ monthly active users. Prior to this, I led Facebook Shop Tab product feed, search & growth teams. I am part of Facebook Better Engineering Steerco and help in upleveling engineering culture, quality & productivity across all of Facebook. I am also an active mentor for Senior Managers and Managers across Facebook. We are hiring for roles across all teams so if you are interested feel free to reach out to me!

Head Of Engineering

2019 - 2020

+ Leading all of Engineering & Technical Operations across Candidate & Client Experience, Subscription Products, Search & Discovery product engineering, Machine Learning, Search, Marketplace, Data Engineering, DevOps, Platform Engineering & IT. + Helped build a Saas Marketplace with Search & Discovery experience and state of the art matching as it’s core offering differentiated across Flex, Basic, Essential & Advanced Subscriptions. + Scaled the team 5x over 4 years + Scaled Subscription ARR from $xM to $xxM in 4 years + In Feb 2019 played a critical role in startup acquisition (incl. due diligence), integration of the team & product into Hired Subscription offering within 9 months of acquisition. + In Sept/Oct/Nov 2020, helped acquisition of Hired by Vettery (Adecco Group) + Helped build Hired’s technology stack for 10x scale. Started with a Ruby on rails monolith and evolved it into a hybrid with Microservices via technologies like React, Python, GraphQL, Kafka, Elasticsearch, Redis, Tensorflow, Sagemaker, Containerized services on CI/CD. + Helped build, focus, align & execute on Hired’s overall strategy in tight-knit collaboration with Hired’s executive team and cross-functional partners. + Established vision & goals for Matching Technology@Hired while inspiring and aligning cross-functional partners.

Senior Director Of Engineering

2018 - 2019

+ Leading multiple teams across Subscription Product, Search & Discovery product engineering, Machine Learning, Marketplace Engineering and Data Engineering. + Helped Hired build a Saas Marketplace product with Search & Discovery matching as it's core offering differentiated across Basic, Essential & Advanced Subscriptions + Scaled the team 3x over 2.5 years + Helped build Hired’s technology stack for 10x scale. Started with a Ruby on rails monolith and evolved it into a hybrid with Microservices via technologies like React, Python, GraphQL, Kafka, Elasticsearch, Redis, Tensorflow, Sagemaker, Containerized services on CI/CD. + Building & executing on Hired's overall strategy in tight-knit collaboration with Hired's executive team. + Established vision & goals for Technology@Hired while inspiring and aligning cross-functional partners.

Director Of Engineering

2017 - 2018

+ Leading multiple teams across Subscription Product, Search & Discovery product engineering, Machine Learning, Marketplace Engineering and Data Engineering. + Helped Hired build a Saas Marketplace product with Search & Discovery matching as it's core offering differentiated across Essential & Advanced Subscriptions + Scaled the team 2x over 1.5 years + Building & executing on Hired's overall strategy in tight-knit collaboration with Hired's executive team. + Established vision & goals for Matching Technology@Hired while inspiring and aligning cross-functional partners.

Senior Engineering Manager, Enterprise Relevance

2016 - 2017

+ Led 50+ engineers focussed on Search & Discovery for LinkedIn Recruiter (from $50 million to $1.1 billion) and LinkedIn Sales Navigator (from 0 to $300 million). + In 2016, led Next-Gen Recruiter (biggest revamp of our Flagship Monetization product) that led to 40% improvement in Search efficiency. + In 2014, led launch of Sales Navigator - LinkedIn’s premier Social Selling product. + Mentored 30+ engineers & managers. + From scratch, built a team of of 30+ Artificial Intelligence (AI) & Machine Learning engineers. + Worked with cross functional leadership team in defining & executing overall product strategy for all Recruiting & Sales solutions business. + Helped close 50+ candidates for LinkedIn, performed 100+ Engineering Manager interviews and 200+ programming interviews. + Organized first ever workshop on Enterprise Intelligence at KDD’16 (premier Data Mining conference). + Part of the core leadership team that performed due dilligence of 10+ startups for acquisition. + Published 32 patents and 4 papers with 320+ citations + Championed the creation of key Artificial Intelligence technology such as Similar Profiles for LinkedIn Recruiter and Decision Maker Score for Sales Navigator. + Worked with cross-functional teams involving engineering, product, marketing & sales teams and executed strategy for all Enterprise products such as LinkedIn Recruiter and LinkedIn Sales Navigator Link to some recent work done by the team + https://business.linkedin.com/talent-solutions/blog/product-updates/2016/the-next-generation-of-linkedin-recruiter-is-here + Identifying Decision Makers from Professional Social Networks: http://www.kdd.org/kdd2016/papers/files/Paper_1089.pdf + Search by Ideal Candidates: Next Generation of Talent Search at LinkedIn: http://arxiv.org/abs/1602.08186

Engineering Manager, Enterprise Relevance

2013 - 2016

Engineering lead for Recommendations for Enterprise Data Products including Sales Navigator and Recruiter. Broadly, my team focuses on automating parts of information discovery and insights to help Enterprise customers become more productive. My team powers Recommendations and Insights across all of LinkedIn's Enterprise Products including Sales Navigator and Recruiter. Enterprise Products + Sales Navigator: https://business.linkedin.com/biz/sales-solutions/b2b-sales-navigator + Recruiter: https://business.linkedin.com/biz/talent-solutions/recruiter Link to some recent work done by the team + http://techcrunch.com/2014/07/31/linkedin-sales-navigator/ + http://sales.linkedin.com/blog/finding-the-right-people-on-linkedin-just-got-easier/ + http://blog.linkedin.com/2014/08/13/how-do-you-stack-up-among-your-industry-peers/

Staff Software Engineer

2013 - 2013

+ Lead engineer for LinkedIn’s recommendation engine system. + Wrote large parts of online serving (1000+ QPS), near-real time personalization using Kafka and offline (map-reduce) computation infrastructure of LinkedIn Recommendation Engine. + Wrote 100s of Java Hadoop map-reduce programs to mine data for analyzing importance of various information signals. + Used advanced mathematics and Machine Learning for training existing and devising new models for improving search & recommendations quality. + Leveraged statistics to do sound metrics and experimental design for gauging effectiveness of various models for improving search & recommendations quality. Links to recent work + http://www.forbes.com/sites/georgeanders/2013/04/10/who-should-you-hire-linkedin-says-try-our-algorithm/

Senior Software Engineer

2011 - 2013

Software Engineer - Recommendation Engine

2010 - 2011

Part of the Recommendation Engine Team. So far, I have worked on Job Recommendation(best jobs for you) and Referral Engine (finds best matches from your network for jobs at your company). In the past 6 months, I primarily focussed on 'Similar Profiles' (given a profile, it finds other top profiles like the original one for hiring). This is my proudest accomplishment at LinkedIn. My talk at Hadoop World 2011 on LinkedIn's recommendation platform: http://www.quora.com/How-do-LinkedIns-recommendation-systems-work

CS Graduate Student

2008 - 2010

I specialized in Artificial Intelligence. Some of the Relevant courses: Machine Learning, Information Retrieval and Web Search, Data Mining, Social Network Analysis, Convex Optimization, Probabilistic Graphical Models, Artificial Intelligence, Distributed Systems Programming, Natural Language Processing, Natural Language Understanding, Scalable Web Programming

Graduate Teaching Assistant

2008 - 2010

+ TA for Course CS 345A (Winter 2010) - 'Data Mining' under Prof. Anand Rajaraman and Prof. Jure Leskovec + TA for Course CS 229 (Fall 2009) - 'Machine Learning' under Prof. Andrew Ng + TA for Course CS 140 (Winter 2009) - 'Operating Systems' under Prof. David Mazières + TA for Course CS 140 (Fall 2008) - 'Operating Systems' under Prof. Mendel Rosenblum

Software Engineering Intern

2009 - 2009

Research Intern

2007 - 2007

Designed and implemented data persistence of a distributed log storage, in Java, for a middle-ware that provides consistency services for collaborative applications.