Jun 2024 – May 2025 · 11 mos · Toronto, Ontario, Canada

Dec 2022 – Jun 2024 · 1 yr 6 mos · Toronto, Ontario, Canada

Jun 2020 – Nov 2022 · 2 yrs 5 mos · Singapore

• As a Machine Learning Engineer, I specialize in recommendation systems and computer vision, building AI solutions that enhance user experience and drive business growth.
• I developed deep learning recommendation models and Click-Through Rate (CTR) prediction systems, optimizing product rankings for E-Commerce channels with 10M+ monthly web visits, boosting cart conversion rates. I also built Variational Autoencoder (VAE) models for product image catalogs, improving recommendations by identifying visually similar products.
• To support these models, I engineered Spark jobs and Airflow pipelines for scalable feature engineering and data extraction. Additionally, I developed image segmentation models with PyTorch for foreground object detection in product images, deploying them on Kubeflow clusters.
• Machine Learning: PyTorch, Scikit-learn, MMDet, Kubeflow
• Data Processing: Hadoop, Spark, Kafka, MongoDB, Airflow

Feb 2020 – Apr 2020 · 2 mos · Singapore

• During my internship as a Research Engineer at A*STAR, I focused on enhancing security and data privacy in deep learning models using federated learning and split learning techniques. I collaborated with a team to develop innovative solutions for preventing sensitive data transmission to central servers. This experience allowed me to gain valuable insights into cutting-edge research in the field of deep learning.

Aug 2018 – Jun 2019 · 10 mos · Bengaluru, Karnataka, India

• In my role as a Software Engineer II at UiPath, I worked on the development of a cloud portal for account management and resource allocation of software robots. Utilizing Java Spring Boot and React, I enhanced user experience and efficiency. Additionally, I was part of the Applied AI team, where I created image classification and detection for unstructured document classification, contributing to the software robots ability to integrate machine learning technologies in automated workflow.

Mar 2016 – Jul 2018 · 2 yrs 4 mos · Koramangala - Bangalore

• In my role as a Software Engineer at Ionos Networks in Koramangala, Bangalore, I worked on a project focused on utilizing raspberry Pi based IOT devices for WiFi analytics in out-of-home advertisements. My responsibilities included developing algorithms for WiFi triangulation and head count using Python, Spark, and Scala to provide key metrics and KPIs for measuring advertisement reach.

Jun 2014 – Mar 2016 · 1 yr 9 mos · Greater Bengaluru Area

• Developed client-side native solution for IP Multimedia Subsystem (IMS) on Android and OS.
• Commercialized solution in flagship Samsung devices.