Applied Science Intern @ JP Morgan ML Center of Excellence Intern
Seattle, WA
June 2024 – Present
  • Developing a robust evaluation system for News RAG Pipelines.
  • Improved robustness and human alignment over open-source baselines and LLM-as-a-judge frameworks.
Data & Applied Scientist @ Microsoft Full-Time
Hyderabad, India
July 2022 – August 2024
  • Built LLM-based pipelines in Bing to improve user query understanding and deliver more relevant answers.
  • Trained and optimized XLMR-based automated entity extractor on 20B Bing webpages (1.25ms latency).
  • Bootstrapped data refresh and triggering pipeline: yielded 1.5M DAU gain (2x YoY).
  • Published SegRank, a novel LLM grounding method reducing hallucinations by 15.7% in BingChat.
  • Honorable Mention at the Executive Challenge in the Microsoft Global Hackathon 2024
  • Won the Award of Excellence for Innovation in Microsoft, IDC for my work on the events datapipeline.
  • Fast-tracked to L60 at Microsoft, earning promotion in 9 months due to exceptional ownership and a proven track record of delivering impactful project outcomes.
Student Researcher @ ETH Zurich & MPI Tübingen Part-Time
Germany
May 2023 – Dec 2023
  • Formulated CausalCite, a novel causal metric for paper citations.
  • Ran large-scale experiments on 2B+ edge and 200M+ node citation graphs.
  • Proposed evaluation metric showing 30.14% better correlation with test-of-time than citation count.
  • Accepted at ACL 2024 (Main Conference), Bangkok; presented as first author.
ML Engineering Intern @ Deloitte AI Center of Excellence Intern
Hyderabad, India
May 2021 – July 2021
  • Modelled probability of success for in-bound opportunities, improving prioritization by 76%.
  • Built an internal MLOps platform for converting notebooks to Kubeflow Pipelines.
ML Engineering Intern @ Zomato Intern
Gurgaon, India
Oct 2021 – Dec 2021
  • Detected fraud in new user accounts (35% of fraud cases) using ML models.
  • Trained seq2seq models on clickstream data to learn user behavior patterns indicative of fraud.
Research Intern @ Video Analytics Lab, IISc Bangalore Intern
Bangalore, India
May 2020 – Nov 2020
  • Built a self-supervised pipeline for generating pose and 3D colored mesh from 2D RGB images.
  • Explored VAEs, AAEs, and Hierarchical AAEs as priors for pose estimation.
  • Used PyTorch3D for differentiable rendering; processed Freihand, HUMBI, and HO3D datasets.
Research Intern @ Complex Networks Research Group, IIT Kharagpur Intern
India
May 2020 – Jul 2020
  • Developed a QA model on the AmazonQA dataset using SentBERT for review filtering.
  • Benchmarked seq2seq and retrieval-based models (including RAG) in PyTorch.