Jun 2025 – Sep 2025 · 3 mos · London Area, United Kingdom · Hybrid

• Designed and deployed an offline “take rate” evaluation pipeline to predict recommender model performance before A/B tests, reducing evaluation time from 1 week to 3 hours and accelerating iteration cycles.
• Pruned and deployed an optimized notification recommender model, reducing inference latency by ~50%, enabling faster notifications and improving user experience at scale.

May 2023 – May 2025 · 2 yrs · Cambridge, England, United Kingdom · On-site

• Overhauled and optimized an existing image clustering pipeline that reduced the processing time by 84%.
• Architectured a pipeline using SOTA models to increase the number of objects detected in an object by 60 times.
• Deployed ML Pipelines on (on‑prem) K8s and AWS Batch using Metaflow.
• Contributed to developing APIs for deployment of the pipeline
• Optimized CICD workflows for machine learning modules with a mix of self‑hosted and github action runners
• Spearheaded in standardizing the Logging system.
• Modularized the prevailing video processing pipeline with a bespoke architecture with 60% faster processing

Feb 2023 – Apr 2023 · 2 mos · Cambridgeshire, England, United Kingdom · Remote

• • Revamped UI design for UniArk (Deployed at: https://uniark.org/) which 93% of stakeholders preferred.

Sep 2021 – Aug 2022 · 11 mos · Chennai, Tamil Nadu, India

• Designed a novel human in the loop learning algorithm that helped in reducing the human biases in datasets that had an improvement of 5%
• on the benchmark datasets.
• Spearheaded and collaborated 5 machine learning projects for stakeholders that revolved around reinforcement and supervised learning.

May 2021 – Sep 2021 · 4 mos · New Delhi, Delhi, India

• Developed a Ticket grading feature for the clients to judge the authenticity of a false positive.
• Implemented bespoke models or pipelines for different use cases using Pytorch, Tensorflow and ONNX over Triton servers with average model
• processing time of 120 milliseconds.

Nov 2020 – Jan 2021 · 2 mos · Noida, Uttar Pradesh, India

• Conducted research on use of AI to improve the success rate of embryo transfer in IVF for humans (15% improvement in accuracy).
• Created a synthetic image generation application using StyleGAN to enhance the existing dataset (10% difference in accuracies).
• Developed a Heat map generation model for inferences learnt by the model using Grad CAM (63% of stakeholders preferred the product with
• this feature).

Jun 2020 – Sep 2022 · 2 yrs 3 mos · New Delhi, Delhi, India

• Authored and published 2 research papers in reputed journals like Springer IJFS and TSP CMC (First Author).
• Guided a team of skilled individuals in research projects and published 1 paper in field of Computer Vision.