Sep 2022 – Feb 2024 · 1 yr 5 mos · Bengaluru, Karnataka, India · On-site

• Backend Engineer at Adobe since September 2022, focused on delivering high-quality software solutions within a dynamic environment.
• Proficient in Java Springboot development, consistently meeting business requirements and enhancing system performance while maintaining critical services with impressive response times.
• Responsibilities encompass a wide range of technical tasks, including comprehensive testing, integration, and automation, as well as expertise in monitoring tools and high-volume service creation.
• Developed extensive automation, integration, and unit tests, resulting in improved software reliability and a reduction in bug occurrences.
• Proficiently utilized monitoring tools such as Grafana, Splunk, and New Relic to continuously monitor system performance, identify bottlenecks, and implement optimizations for enhanced efficiency and stability.
• Leveraged Apache Storm to design and implement a high-throughput notification service capable of handling 40,000 requests per minute (rpm), significantly improving the user experience.
• Responsible for maintaining a mission-critical service related to license information, achieving a remarkable response time of less than 30 milliseconds (ms) to ensure uninterrupted service availability and meet strict SLAs.
• Collaborated effectively with cross-functional teams, including developers, product managers, and operations, to drive project success and align technical efforts with business objectives.

Jun 2021 – Sep 2022 · 1 yr 3 mos · Bengaluru, Karnataka, India · Remote

• Developed AOSP Android apps in Java and created Android system apps tailored for laptops.
• Played a pivotal role in enhancing and adding features to the AOSP file manager app designed specifically for Android-based laptops.
• Led the development of the StickyNotes app from inception, building it entirely from scratch using Java for Android-based laptops.
• Took ownership of app and feature development, demonstrating a high level of responsibility and leadership within the team.
• Actively contributed to enhancement proposals and the expansion of capabilities for various applications.
• Followed agile development practices, including Scrum, to ensure efficient and collaborative project management.

May 2020 – Jul 2020 · 2 mos · Pune, Maharashtra, India · Remote

• Proficiently conducted data analysis using Python, processing data sourced from APIs connected to ECUs (Electronic Control Units) installed in various vehicle models.
• Developed machine learning models, including Support Vector Machines (SVM), K Means Clustering, Decision Trees, and XG Boost, to monitor the lifecycle of engine oil.
• Demonstrated a strong ability to work independently, taking the lead in most data analysis tasks.
• Effectively communicated findings and inferences derived from data analysis to address business use cases, facilitating data-driven decision-making processes.

Oct 2019 – Mar 2020 · 5 mos · Raipur, Chhattisgarh, India · On-site

• Research and Development Intern at Logy.ai, with a tenure of 6 months from October 2019 to March 2020.
• Conducted research focused on object detection methods for diagnosing malaria from blood smear images.
• Developed a user-friendly AutoML application, using Django and TensorFlow, to facilitate model training for computer vision projects in the medical field.
• Demonstrated a high level of independence in data analysis tasks and effectively presented findings for business use cases.
• Created an integrated object detection pipeline within Django, streamlining data preprocessing and modeling for an AutoML portal dedicated to disease detection.
• Proposed and implemented a two-stage Faster R-CNN (F-RCNN) based model, significantly enhancing precision for Malaria Parasite detection from 40% to 80%.
• Actively engaged in daily responsibilities involving literature review and research paper analysis, contributing to the continuous improvement of Malaria Detection Research.

May 2019 – Jul 2019 · 2 mos

• CS Summer Intern at Artificial Visual Labs, with a 3-month tenure from May 2019 to July 2019.
• Developed a proof-of-concept (POC) makeup emulation application in C++, allowing users to apply virtual makeup, including eyeliner, blush, lipstick, and eye-shadow, to selected images of their faces.
• Conducted data analysis on CCTV footage from a factory to assess wood quality.
• Analyzed CCTV data from a hotel lobby to track human movement and provide analytics on the movement of people.
• Spearheaded the development of multiple proof-of-concepts (POCs) in Python and C++, addressing various computer vision tasks, showcasing a versatile skill set.
• Contributed actively to presentations and research, leveraging computer vision techniques to solve practical problems and enhance the functionality of existing systems.