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Summary

Senior ML Engineer @ Guardant Health  || Computer Vision @ Deep Learning Analytics  || 

MTech(R) (CS) @ IIT-Hyderabad  ||  SWE @ Grey Orange Robotics  ||  BTech (CS) @ BITS-Pilani  ||  http://arxiv.org/abs/2012.07735

Work experience

Guardant Health, India
Oct 23Present

Senior ML Engineer (Remote)

  • Document Classification at Scale: Automated classification of medical documents using AWS Textract, Batch/Glue jobs, and SNS-SQS, reducing end-users' search time. System is able to handle large volumes efficiently.
  • Appeal Prioritisation Model: Built an appeal scoring model with SHAP explainability, helping the reimbursement team prioritise appeals and maximise claim recovery. Both predictive and prescriptive in nature.
  • Signature Extraction Project: Extracted patient signatures from TRF forms using segmentation models. Worked extensively to reduce error by 30%, important for manual cost cutting.
  • NL-to-SQL System for Business Development: Designed an LLM-powered query system with RAG and prompt engineering, converting natural language queries into SQL to answer queries and derive statistics for BD team.
Deep Learning Analytics, Toronto
Aug 22July 23

Senior Computer Vision Engineer (Remote)

Client: S3Global – Sports Analytics on Soccer Matches

  • Built CV models for object detection, segmentation, pose-detection, and team classification on real-time camera feeds for European football clubs.
  • Detr (ViT) Optimization: Achieved 30% speed enhancement using sparsity and 50% throughput improvement by applying mixed precision and TensorRT optimizations.
  • HRNet for Pose Detection: Implemented pose visualization and correction using 3D triangulation and mmpose with COCO datasets.
  • DeepStream Realtime Pipelines: Developed and optimized pipelines for real-time performance on various architectures, reducing latency significantly.
  • Worked on event classification (e.g., pass, goal) and ported eventing pipelines to real-time.
  • Expertise in camera syncing using OpenCV, Ffmpeg, Docker, and Redis for processing multiple camera feeds in sync.
IIT Hyderabad, IN
20192022

Research Assistant, Machine Learning

With focus on Deep-Learning Models, worked at intersection of Computer Vision and Astrophysics.
Neural Ordinary Differential Equations (NODE), Variatonal Inference, Few-Shot Learning etc.

Publication: https://arxiv.org/abs/2012.07735 (26 Citations in 2 yrs)

Tokyo University
Dec 20Jan 21

ML Intern

Looked into new NODE architecture for better accuracy and generalization in NODE.

Grey Orange, Gurugram
July 16July 18

Software Development Engineer

Built Manager Dashboard from scratch. Millions of Orders fetched, displayed, sorted and filtered, all
real-time. Built using Flask, Postgres, SQLAlchemy and Tornado, with React front-end.
pub/sub model: pushed data over multiple channels simultaneously (over web-sockets)
● filtering and sorting millions of orders using SQLAlchemy as ORM
● Prediction System: notify possible breach of order fulfilment

Education

MTech (R) (CS), IIT-Hyderabad
20192022

Deep Learning, Computer Vision, Machine Learning, Reinforcement Learning

3D Computer Vision Summer School, IIIT Hyderabad
May 2022

3D Representations, Point-Clouds, MeshLab, Open3D, PIFu, NeRF

BITS-Pilani, Pilani
20112016

 BTech Computer Science + MSc Physics

Publications

Projects

Skills

Cloud Technologies -: AWS (Textract, Bedrock, SageMaker, Lambda, Airflow, Batch, Glue)

ML Libraries/Techniques: PyTorch, RAG, QLoRA

CV Libraries/Models: DeepStream, TensorRT, Detr, YOLO Series

Python Frameworks: Flask, SQLAlchemy, Postgres, Terraform, OTP (Erlang)

Academic Achievements

IIT-JEE (2011) rank 7192 (among 4.5 lakh students)

AIEEE (2011) rank 8154 (among 6 lakh students)