I'm a Software engineer at Nutanix, working on cool distributed systems for VM management. Peviously, I worked at Walmart in the eCommerce and logistics domain. I graduated from BITS Pilani in 2021 with a BE in Computer Science and have about 3.5 years of full-time experience.
My core skills are:
‣ Building scalable web services using Java, Springboot, GraphQL.
‣ Distributed systems.
‣ Building data processing pipelines using Kafka, Spark.
‣ Full-stack Development with ReactJS and Django with backend on Cloud(AWS) or Serverless(Firebase).
‣ Building Deep Learning applications and deploying Machine Learning models at scale.
‣ Building reliable and resilient services with Monitoring, Alerting and Disaster Recovery processes in place.
I love exploring tech and have done projects across Full-stack development, Deep Learning and Robotics. Nowadays, Distributed systems facinate me the most.
Get in touch at anshulsoodnet@gmail.com if you want to collaborate on a project or have an exciting opportunity for me.
Feb 2024 - Present
Enhancing features and performance of the AHV VM Control Plane.
Tech Stack: Go, Python, Bash
Aug 2023 - Jan 2024
‣ Built SWW 2.0 Billing system. SWW - Ship with Walmart, is a multi-tenant SaaS product for providing shipping services with 3rd party carriers.
‣ Involved in end to end product development from requirements gathering, design (LLD) and coding.
‣ Made the complete pipeline Highly Available through multi-region data replication, multi-region Crons and Kafka failover.
‣ Built a solid Reconciliation System to tackle the challenges associated with a distributed system as well as ensure the accuracy of transactions processed through the Billing System.
Tech Stack: Java, SpringBoot, Kafka, Azure
Jul 2021 - Jul 2023
‣ Developed a GraphQL BFF for a seller onboarding application and integrated it with the API Gateway.
‣ Built pipelines for various initiatives like: Catalog Porting between international markets, Generating Duty tax reports to help sellers price their products profitably, Shortlisting sellers to provide opportunities based on their performance metrics.
Tech Stack: Java, SpringBoot, Spark, GraphQL, Azure
Aug 2020 - Dec 2020
‣ Created a distributed pipeline for serving Deep Learning models to provide Number Plate Recognition at scale.
‣ Followed microservices pattern to make each model independently scalable and handle multiple video streams in parallel.
‣ Solved the challenges of Ordered Processing, Stateful Processing and Transactions in a distributed application.
‣ Technologies: Python, Java, Kafka, gRPC, Redis, Docker, MySQL
May 2020 - Jul 2020
‣ Created a mechanism to report which Advertising campaigns must be paused or resumed, depending on the item availability in inventory.
‣ Optimized performance using parallelization and batching while ensuring the API rate limit is not breached.
‣ Technologies: Java, SpringBoot, Hibernate, Thymeleaf, MySQL
2017 - 2021
Activities and Societies: Electronics and Robotics Club, Spree 2018 (Sports Fest) Organizing Committee
[In Progress] A simple service to store logs built with scalablity in mind by applying distributed systems concepts like Service Discovery, Coordination with Consensus and Load Balancing.
A feature-rich travel blogging site with Authentication, Rich text editor, Image upload support etc. features. Built with ReactJS and deployed on AWS. (Backend currently unavailable due to expiry of free-tier)
Implemented a basic memory subsystem in C as a part of Data Storage Technologies course. It consisted of a TLB, 2 level caching and a Main Memory with Paging.
Tweets are fetched from the Twitter API and their sentiment is analyzed to predict the relative demand for products at a chosen locality. This info can help a retailer stock its inventory accordingly.
Performs real-time engagement intensity prediction using gaze and pose estimation. The feed is segmented into 10-second video clips, from which facial features are extracted, and then a neural network determines the level of engagement at the given instant.
A solution for detecting if a worker is wearing safety gear while working at the workshop, using CCTV cameras. Uses YOLO for object detection and Deep SORT for person tracking. Has a dashboard built with Tkinter to display real-time feed and show alerts.
Developed a localization system for an autonomous bot developed by the college Robotics Club. It polls data from an Optical Displacement Sensor, Gyroscope, Accelerometer, Magnetometer, and fuses them using Kalman filtering. Used Raspberry Pi as the onboard computer.
Java, SpringBoot, Python, Django, JavaScript, React.js, C, Go
Azure SQL, MySQL, PostgreSQL, Google Firestore, Redis
Kafka, GraphQL, SQL, gRPC, Spark, Docker, Git, Bash, AWS, Firebase, Deep Learning, Data Mining
Walmart Global Tech, July 2022
Walmart Global Tech, Nov 2021
Department of Science and Technology India, Dec 2011