Work Experience

Software Engineer

SpectroCloud

May 2025 – Present

  • Developing high-performance APIs and backend systems for a Kubernetes management platform that scales to 10,000+ clusters
  • Implementing OpenTelemetry integration for comprehensive observability, including metrics collection and distributed tracing across microservices
  • Optimizing system performance for critical infrastructure where Kubernetes cluster management is vital for enterprise customers
  • Building scalable backend services that handle large-scale Kubernetes operations with emphasis on reliability and performance

Teaching Assistant

Manning College of Information and Computer Science, UMass, Amherst

June 2024 – Nov 2024

  • Evaluated and graded assignments, projects, and exams, ensuring accurate assessment of students' understanding of software engineering principles (COMPSCI-520).
  • Provided constructive feedback to students, helping them improve their coding practices, design techniques, and problem-solving skills.

Graduate Student Researcher

Human Centered Robotics Lab, UMass, Amherst

June 2024 – Nov 2024

  • Optimized a model for frame-level fault detection in collaborative autonomous systems, processing 30 images per timestep from 5 agents in the DeepAccident dataset.
  • Conducted an in-depth analysis of dataset structure and identified key challenges impacting detection outcomes.
  • Designed and implemented a denoising-based fault detection model with Vector Quantized GANs and Graph Attention Networks as pre-training, exploring enhanced learning for fault detection in multi-agent autonomous systems.
  • Optimized a non-linear MPC-WBIC controller through semi-black box fine-tuning, tailoring it for improved performance on the Go1 robot platform.

Dining Hall Supervisor (Part-Time)

Auxiliary Enterprises, UMass, Amherst

Sep 2023 – Dec 2024

  • Handled 2000+ students per meal session
  • Led and motivated team members to maintain high performance and productivity, ensuring smooth operations across all work areas.
  • Strategically managed employee break schedules to balance workload and optimize efficiency.
  • Demonstrated strong attention to detail by ensuring allergens were accurately identified and communicated, fostering a safe and compliant work environment.

Software Development Engineer - I

Eagleview, Bengaluru

Aug 2020 – Dec 2022

  • Assisted in designing and led implementation of an event-based notification service handling push, email, and iOS notifications via AWS SQS and SNS, supporting 1,000+ concurrent requests.
  • Gained proficiency in C# and delivered critical release APIs within one week.
  • Delivered 6+ Golang and Python microservices, collaborating with cross-continental agile teams.
  • Contributed to migrating a legacy platform to a serverless orchestrator using AWS Step Functions and Lambda, reducing service time from 3 hours to 45 minutes.
  • Achieved 60% latency reduction for large file downloads by implementing gRPC stream APIs.
  • Enhanced service performance and resolved critical bugs through regular load and performance testing.
  • Translated business-critical MATLAB code handling geospatial data to Python, increasing scalability and reducing latency by over 70%.
  • Participated in the full SDLC of Assess, an online imagery inspection tool with a $1M+ projected revenue.
  • Proposed OpenTelemetry integration for serverless tracing, improving logging and debugging capabilities.
  • Participated in code reviews to ensure clean, tested, readable and maintainable codebase to maintain 90% code coverage.

Software Development Engineer Intern

Eagleview, Bengaluru

Jan 2020 – June 2020

  • Delivered 15+ APIs for a critical process and improved API documentation, reducing cross-team dependency and cutting development time by 15%.
  • Presented a study on ElasticSearch-Logstash-Kibana (ELK) stack for observability, demonstrating its potential to trace points of failure within 30 minutes and deliver key analytical insights.
  • Proto-typed a dashboard to automate version tracking, cutting manual checks and documentation time by 50%.

Research Intern

Center for Cloud and Big Data, PES University, Bengaluru

May 2018 – Aug 2018

  • Researched on federated clouds using OpenStack.
  • Conducted a feasibility study of federated container service using Mesos in Openstack.

Education

MS in Computer Science

University of Massachusetts, Amherst

GPA: 4.0/4.0

Relevant Coursework

Distributed Systems Software Engineering Reinforcement Learning Internet Security Advanced NLP Robotics

B.Tech in Computer Science and Engineering

PES University, Bengaluru, India

GPA: 8.31/10

Relevant Coursework

Data Structures Computer Networks Cloud Computing Machine Learning Database Systems Operating Systems

Projects

Distributed Rate Limiter

A scalable rate-limiting system built with gRPC and Kubernetes for distributed applications.

  • Designed a gRPC-based rate-limiting system using Redis for storage
  • Implemented a FastAPI-based dummy service to validate request throttling
  • Developed a Kubernetes operator to dynamically configure rate limits via CRDs
  • Deployed services using Docker and Kubernetes with automated policy enforcement
gRPC Redis Kubernetes FastAPI Docker

Human Following Robot

An intelligent robot system capable of real-time human tracking and following using computer vision and machine learning.

  • Developed a sophisticated human-following capability for a holonomic robot equipped with an RGB-D camera
  • Leveraged advanced machine learning models such as YOLO-v7 for object detection, SuperPoint for feature extraction, and a PID controller for precise movement
  • Integrated computer vision and control systems for real-time human tracking in dynamic environments
Human Following Robot
YOLO-v7 SuperPoint PID Controller Computer Vision ROS

Quote Classification and Interpretation

An NLP system for multi-label classification and interpretation of quotes using state-of-the-art transformer models.

  • Fine-tuned Transformer models like BERT, GPT-2, and T5 for multi-label classification of quotes
  • Explored prompting techniques on T5 and Gemma models to enhance quote interpretation
  • Improved model accuracy and efficiency through extensive analysis of results
BERT GPT-2 T5 Gemma PyTorch

Stock Exchange Application

A distributed systems prototype for stock trading with fault tolerance and leader election mechanisms.

  • Prototyped a stock trading application in Python to experiment with distributed systems concepts
  • Implemented multithreading and leader elections for a realistic trading simulation
  • Tested algorithms for fault tolerance and system optimization
Python Multithreading Distributed Systems Fault Tolerance

ML Model Optimization for Predictive Analysis

A comprehensive machine learning pipeline with custom models and hyperparameter optimization for predictive analytics.

  • Developed custom machine learning models, including Neural Networks, Random Forests, and K-Nearest Neighbors
  • Applied hyper-parameter tuning and optimization to maximize model performance
  • Generated F1 Score graphs for data-driven decision making
Neural Networks Random Forest K-NN Hyperparameter Tuning Scikit-learn

Cultural Dimensions in AI Ethics

Research on the impact of cultural dimensions on AI decision-making in autonomous vehicles using the Moral Machine experiment data.

  • Explored moral dilemmas in autonomous vehicles, training AI models for ethically acceptable decision-making using data from the Moral Machine experiment
  • Evaluated model performance by analyzing accuracies across multiple training techniques and methodologies
  • Investigated cultural influence on AI decisions by incorporating Hofstede's six dimensions of national cultures during data preprocessing
AI Ethics Cultural Analysis Moral Machine Hofstede Dimensions Research