Dheemanth Bykere Mallikarjun
Santa Clara
Summary
Accomplished Senior software Engineer at LinkedIn with 6+ years of backend software development. I design & develop E2E features pertaining to Ad tech stack. I'm passionate about building distributed application services at scale and well versed with enhancing system performance metrics .
Overview
7
7
years of professional experience
Work History
Senior Software Engineer
LinkedIn
08.2021 - Current
- Designed & developed an accelerated ad campaign stack to facilitate the member boosting feature in order to boost organic posts as ad entities. Integrated with Apple's advanced commerce API to support In-app purchase of boosting credits with dynamic pricing, leading to revenue upside of $29M in the initial ramp. Expanded the audience reach for 65% of SMBs
- Developed backend service to serve realtime ads in video feed/chaining involving ads targeting, BMO filters, bidding/budgeting, pacing, L1/L2 rankers, ad auction, frequency capping & ad tracking. Increased immersive video ads 2s view rate by 44%, 24% increase in website visit rate and 3x increase in video ad completion rate for engagement objectives
- Developed distributed application software for job ingestion, job promotion & job distribution services
- Enhanced job lifecycle management by designing & developing job suspension, job reingestion feature which reduced job recreation rate from 67.51% to 4.71%, DB inserts from 30.14% to 15.63%, increased Total Qualified Applications (QA) by +6.99%, Paid Job Chargeable views by +9.25%, Applies total chargeable by +9.09%
- Investigated & enhanced GG replication lag in jobs DB which reduced the DB writes by 70% & lag was reduced from average of 5 min to < 5s & increased the job ingestion QPS by 23%
- Led the design & developed the staffing customer basic job restriction feature spanning across job promotion, job search, job notification services which increased revenue from job slot by +35%
- Investigated the bottlenecks & enhanced API close job flow from sync to async which reduced the p99 latency from 300 ms to < 50 ms
- Led the design of enhanced local & global job deduper pipeline which reduced duplicate jobs by 43%
- Developed a generalized A/B test framework utilizing the nearline & offline flow architecture to conduct A/B tests to gauge impact of onboarding segmented jobs. Readout inferred +1.5% SWI Quality Jobs (216K) which led to: 1.8% Jobs Sessions (0.12% Site Sessions), 1.1% Jobs WAU (0.11% Site WAU), 3.0% Job Views, 4.1% Applicants, 5.4% Job Applies
- Investigated cross colo race conditions leading to job attributes inconsistency, designed a nearline flow leveraging CDC stream to alleviate it which reduced the inconsistency from 36% to less than 5%
- Designed & developed job distribution pipeline providing a platform to promote job campaigns increasing the job weekly active users by +27%
Member of Technical Staff 2
VMware
07.2019 - 08.2021
- Developed dataplane module for the NSX Edge gateway service using multithreaded lockless programming(Read Copy Update)
- Developed optimized Receive side steering (RSS) module to load balance dynamically between CPU cores based on consistent hashing & also prioritize control traffic for high availability service. This increased the control traffic QPS by +23.8%
- Developed distributed control flow cache to bypass the packet processing pipeline, accelerating the packet forwarding service & choose optimized route for multicast streaming using event driven architecture
Education
Master of Science - Computer Engineering
Arizona State University
Tempe, Arizona05.2019
Skills
Java, Python, Scala
MySQL, PostgreSQL
Cassandra, MongoDB, DynamoDB
Redis, Couchbase, Memcached
Kafka, RabbitMQ
Apache Spark, Apache Flink
Temporal
Timeline
Senior Software Engineer
LinkedIn
08.2021 - Current
Member of Technical Staff 2
VMware
07.2019 - 08.2021
Master of Science - Computer Engineering
Arizona State University