About Me
As a Founding Engineer and Machine Learning specialist, I've architected software and intelligent engines that are meant to be deployed.
Why Hire Me?
I am a master in the art of turning coffee into code and the art
of failing upwards
San Francisco, CA
Technical Skills
Languages
Python, C++, SQL, Java, Dart
ML Frameworks
PyTorch, TensorFlow, Scikit-learn, OpenCV, Transformers
Infra & MLOps
Docker, AWS (EC2, S3), Celery, Temporal, GitHub Actions (CI/CD)
Data & Backend
PostgreSQL, PySpark, Databricks, Django, FastAPI, Redis, Pinecone
Core Competency
Edge AI, Model Quantization, Latency Optimization, Parallel Computing
Professional Experience
Grove Safety San Francisco, CA
Founding Engineer (Machine Learning)
August 2024 – October 2025- AI Optimization: Architected the end-to-end inference engine for real-time object detection (YOLO, EfficientDet) and audio classification (YamNet). Achieved 30ms latency on resource-constrained devices via quantization.
- ML Pipeline Design: Built the complete MLOps lifecycle from data ingestion to deployment. Engineered automated quantization pipelines to convert models into edge-optimized formats (TFLite/ONNX).
- LLM Workflow: Built multistep LLM workflows using Temporal, Reducto for document processing, implementing typo-tolerant search (pg_trgm), centralized observability with Sentry and CI/CD with GitHub Actions.
- Scalable Backend: Engineered a high-throughput Django backend using Celery for asynchronous inference tasks and WebSockets for real-time prediction streaming.
Finarb Kolkata, India / California
SDE-AI
January 2022 – December 2022- Predictive Modelling: Deployed an ensemble model (XGBoost + Neural Networks) for customer retention, utilizing hyperparameter tuning to optimize for recall in the healthcare industry.
- ML Modelling: Developed ML model for automated defect detection using sensor data from production robots, achieving 93% accuracy in identifying broken pills and reducing QA costs.
- Inference API Optimization: Built a production ML serving API using Flask. Reduced response time by 50% (to <2s) through multi-worker architecture and database query optimization.
- Big Data Pipelines: Designed ETL pipelines using PySpark on Azure Databricks, integrating data from 5+ sources.
JPMorganChase / Wiley India
Full Stack Engineer and Intern
May 2021 – December 2021- Developed front-end components for web applications using Java, Spring, and Spring Boot, contributing to an agile life cycle.
- Implemented Eureka for microservice architecture and load balancing, optimizing application performance and ensuring high availability across distributed systems.
- Built RESTful APIs with comprehensive error handling and validation, following enterprise-level security and coding standards.
Self Employed · Freelance Hyderabad, Telangana, India / Remote
Tech Consultant
March 2020 – November 2021- Developed 5+ mobile, web applications and published 2 machine learning-powered apps to Google Play Store, resulting in over 10k+ downloads.
- Integrated machine learning models into web applications using Django and Flask frameworks, hosted on AWS EC2.
- Utilized Docker for containerization and Elasticsearch for efficient data retrieval and search functionality.
Swecha Hyderabad, Telangana, India
Data Science Intern
May 2019 – June 2019- Led Agro-Analyzer, an open-source project aimed at helping farmers make informed decisions about which crops might yield better profits based on weather forecasts and previous year prices. Worked with a team of 5 to predict crop prices using NumPy, Pandas, TensorFlow, and Bokeh.
- Collected and analyzed 2 years of agricultural data for 15 high-yield crops to forecast costs over the next year. Delivered interactive visualizations in Bokeh to communicate data insights about crop trends, enabling farmers to plan their crop cycles effectively.
Education
Rice University
January 2023 – May 2024Master of Computer Science (ML Major)
Houston, TX
Role: Graduate Intern & Teaching Assistant (Machine Learning & Deep Learning)
GITAM University
June 2017 – April 2021Bachelor of Technology in Computer Science
Hyderabad, India
Projects & Academic Experience
Cardiomyopathy Diagnosis Using ML
- CV Pipeline: Automated echocardiogram analysis by implementing RGB isolation, outlier detection, and polynomial regression to extract six heart strain maps.
- Diagnostic Model: Developed ensemble classifier (CNN, SVM, RF) to detect pediatric diastolic dysfunction, achieving 0.9 AUC on an imbalanced medical dataset.
Reinforcement Learning & Parallel Computing
- Developed a MiniGrid agent solving complex tasks using reward shaping and fine-tuning.
- CUDA Kernel Development: Designed data-parallel kernels for sparse array compaction optimizing memory reorganization on GPUs.
- Distributed Systems (MPI): Implemented communication-optimal 2.5D Matrix Multiplication algorithm using MPI.
Price Prediction using NLP & LSH
- Leveraged Natural Language Processing and Locality Sensitive Hashing algorithms to predict real-world marketplace prices efficiently.
Computer Vision to Reduce Food Wastage
- Applied CV models to monitor and reduce food wastage by accurately identifying produce states.
Community & Certifications
Community Engagement
- GLUG President (GITAM University): Led 50+ member community; delivered presentations to 700+ students (2019-2021). Co-founded with FSMI.
- Tapia STEM Camp Volunteer (Rice University): Mentored underrepresented minorities in STEM disciplines (2023-2024).
- Engineers Without Borders (GITAM): Student Coordinator. Raised funds for rural infrastructure, ran flood relief camps and digital classes (2017-2019).
- CSGSA Treasurer (Rice University): Coordinated event logistics, timelines, budgets for grad student association events.
Certifications & Awards
- Wiley Edge: Software Developer Program (Nov 2021)
- LearnQuest: Cloud Computing Basics (Dec 2020)
- Alberta Machine Intelligence Institute: Machine Learning Algorithms: Supervised Learning (Dec 2020)
- University of Michigan: Python Data Structures (Dec 2020)
- Inter-school Badminton: Runner-up Champion