experience

industry roles and research internships, in reverse chronological order.

Industry

  • Amazon

    May 2026 – Aug 2026

    Software Development Engineer Intern · Alexa Audio

    Seattle, WA

    • Built A3LS, an accent-audio testing service generating TTS across 13 accents and scoring per-accent ASR degradation (WER/AIER), via a Step Functions pipeline that fans out over tens of thousands of (utterance × accent) items per run.
    • Shipped a React/Cloudscape analytics dashboard over a CloudWatch metrics API, surfacing per-accent WER/AIER, latency percentiles, and GPU/concurrency, with skeleton loading and caching for instant loads.
    • Authored HLD/LLD design docs and drove cross-team design reviews to integrate an accent dimension for injecting synthetic audio into production ASR test runs.
    • Delivered across 80+ code reviews spanning 4 Brazil packages, owning CI/CD via Pipelines/Apollo.
    JavaAWS Step FunctionsLambdaSmithyCDKReactCloudWatch

  • Nomura

    Jan 2025 – Jun 2025

    Software Engineering Intern

    Mumbai, India

    • Worked on an internal budgeting and financial planning application used across multiple teams.
    • Resolved over 40 JIRA tickets in 6 months, focusing on performance improvements, bug fixes, and user experience.
    • Delivered features using React on the frontend and Spring Boot for backend services.
    • Collaborated within an Agile team, using Jenkins for CI/CD and SQL for data-layer operations.
    ReactJava Spring BootSQLJenkinsAgile

  • AIAssistant Startup

    Aug 2024 – Dec 2024

    Backend Intern

    California · Remote

    • Developed backend solutions for multiple clients at a startup focused on voice and agentic AI.
    • Built integrations across Twilio, Deepgram, and ElevenLabs.
    • Produced prototypes for client demos, including call summarization, healthcare assistants, and lead-generation voice systems.
    FastAPIPythonTwilioDeepgramElevenLabs

  • Ernst & Young

    May 2024 – Aug 2024

    Data and GenAI Intern

    Pune, India

    • Worked on business and technical solutions for Fortune 100 clients driven by Generative AI.
    • Developed a chatbot with a RAG pipeline over 10,000+ documents, improving search efficiency by 200% via metadata filters that narrowed the search space from 10,000 documents to 50.
    RAGPythonGenAIVector Search

  • Jio Platforms Limited

    May 2023 – Jul 2023

    Artificial Intelligence Intern

    Mumbai, India

    • Worked on "Improving Operations with AI," focused on improving business operations using advanced AI.
    • Designed and deployed recommendation algorithms, including Apriori, to enrich decision-making.
    • Built a web application presenting the implemented features to key stakeholders.
    PythonRecommender SystemsApriori

Research Labs

  • IIT Kharagpur

    Apr 2024 – Aug 2024

    Research Intern · Prompting and LLMs

    Remote · Pune, India

    • Participated in red-teaming to identify and analyze safety limitations and vulnerabilities of LLMs.
    • Implemented chain-of-thought strategies to strengthen LLM robustness and ethical application, with custom Python scripts for automated output evaluation.
    • Evaluated jailbreak robustness across ChatGPT, Gemini, Nous-Hermes, Mixtral Instruct, and Cohere Coral using custom multilingual prompts, cross-evaluating with multiple HuggingFace sentiment models.
    Red-TeamingLLM EvaluationPythonHuggingFace

  • IIT Indore

    Jan 2024 – Apr 2024

    Research Intern · Natural Language Processing

    Remote · Pune, India

    • Extracted critical information from disaster-related tweets using advanced text summarization, reducing a dataset of 3,000 tweets to the 40 most crucial.
    • Applied large language models and integer linear programming to improve summarization accuracy and efficiency.
    • Engineered a flood detection project applying segmentation techniques to improve classification outcomes.
    NLPSummarizationILPSegmentation

  • RCI — DRDO

    Jul 2023 – Aug 2023

    Machine Learning Intern

    Hyderabad, India

    • Used Splunk and Kafka to improve the system's security measures.
    • Performed log analysis and anomaly detection on over one million logs, reducing major outliers to a few hundred; the proof of concept was showcased to senior scientists for possible production deployment.
    • Applied One-Class SVM, KMeans, and Isolation Forests to improve detection accuracy.
    • Developed a dynamic web application with Flask, Bootstrap, and vanilla JS.
    Anomaly DetectionSplunkKafkascikit-learnFlask

For education, publications, and skills, see the full CV.