Vaibhav Ghadge

Software Engineer

Pune, Maharashtra, India5 yrs 9 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in backend systems and data platforms.
Achieved 2x increase in click-through rate for recommendation system.
Strong advocate for functional programming and diverse language expertise.

Stackforce AI infers this person is a Backend-focused Software Engineer with expertise in data-driven applications and distributed systems.

Contact

vaibhav.ghadge@helpshift.com LinkedIn

Skills

Core Skills

Go (golang)Python

Other Skills

AlgorithmsApache FlinkApache SparkArchitectureClojureComputer ScienceData StructuresDatabase ModelingDistributed SystemsDockerEngineeringFlaskFunctional ProgrammingGitHaskell

About

About: Experienced Software Engineer with expertise in backend, distributed systems, & data platforms Primary Tech Stack - Python, Golang , Java , Clojure - Redis, Redshift, MongoDB, HBase, Elasticsearch, Postgres - Spark, Hadoop & family! - POCs, benchmarks, metrics, CICD - TDD, pair programming & SOLID Huge fan of functional Programming and Golang. I enjoy all its facets like programming, data structures, and algorithms, databases, systems, etc. - In programming languages follows this philosophy - One should know at least a couple of programming languages of different paradigms in-depth (in my case Golang and Python - OOP and functional paradigms (Clojure)) and be flexible enough to adopt one over another in different contexts Github: https://github.com/vaibhav2ghadge

Experience

Helpshift

2 roles

Software Engineer ll

Jan 2023 – Present · 3 yrs 2 mos · Remote

Software Engineer

Aug 2021 – Dec 2022 · 1 yr 4 mos · Remote

Agrostar

2 roles

Software Development Engineer

Promoted

Apr 2020 – Jul 2021 · 1 yr 3 mos · Pune, Maharashtra · Remote

Built a Personalized Post Recommendation System
Designed and implemented a post recommendation system that personalizes content based on 12 different user-related parameters.
Developed a real-time recommendation component optimized for weak and intermittent mobile connections.
Delivered multiple iterations of the recommendation engine, with a strong focus on improving key metrics. Collaborated closely with product managers, the CEO, and other stakeholders to analyze data and guide product direction.
Conducted A/B testing and experimented with various algorithms, refining the recommendation logic using click-through matrices.
Prioritized performance and memory optimization, ensuring smooth functionality even on low-end devices.
Achieved 2x increase in click-through rate compared to the previous recommendation system.
Technologies Used: Go (Golang), Python, gRPC, MongoDB, Redis, Flask, Kafka, Redis Queue