Named Entity Recognition (NER)
→
Summary
Trained a robust BiLSTM-CRF model for Named Entity Recognition, addressing class imbalance and achieving high accuracy.
About
Highly accomplished Machine Learning Engineer and Data Specialist with a proven track record of developing and deploying advanced AI/ML solutions, optimizing data pipelines, and enhancing software systems. Expertise spans across large language models (LLMs), generative AI, speech recognition, and complex data analytics. Adept at leveraging Python, Java, and cloud platforms (AWS, GCP) to drive impactful results and improve system performance by significant margins. Seeking to apply innovative technical skills to challenging roles in AI/ML engineering and data science.
Work
In The Loop
|Machine Learning Engineer, LLM
→
Summary
Developing and scaling advanced LLM-based solutions for apparel attribute prediction and multimodal inference services.
Highlights
Spearheaded the implementation of a post-inference mapping layer for apparel attribute prediction, achieving over 95% label match accuracy across 3,000+ SKUs by accurately translating model predictions into client-specific taxonomies.
Engineered and scaled multimodal Large Language Model (LLM) inference services on Kubernetes, significantly improving concurrent request handling efficiency by 20%.
Easley-Dunn Productions
|Software Engineer, Data
→
Summary
Focused on integrating player telemetry, optimizing game performance, and enhancing player engagement through data-driven insights and A/B testing.
Highlights
Integrated advanced player telemetry and critical gameplay features for the Spurpunk game (Unity/C#), which reduced data tracking delays by 25% and accelerated performance tuning across production and test environments.
Conducted in-depth analysis of player behavior to pinpoint resource imbalances, then designed and executed targeted A/B tests that directly informed level design enhancements, resulting in a 15% improvement in player engagement.
Alzheimer's Therapeutic Research Institute
|Software Engineer, ML
→
Summary
Developed and optimized AI/ML-driven solutions for speech recognition and data visualization, contributing to research initiatives.
Highlights
Authored a comprehensive comparison report evaluating over 15 open-source speech recognition libraries, focusing on performance metrics, resource allocation, and conducting benchmark analysis across multiple languages to inform strategic technology decisions.
Developed and optimized a robust video transcription pipeline incorporating speaker distinction, which successfully reduced timestamp discrepancies by 20% and improved transcription accuracy.
Designed and implemented scalable REST APIs using Django Rest Framework and an interactive LIMS Dashboard with D3.js, adhering to stringent software design patterns and test-driven development principles.
JoshTalks
|Software Engineer
→
Summary
Engineered real-time communication features, optimized API performance, and streamlined deployment processes.
Highlights
Led the integration of speaker settings for a real-time group voice call feature utilizing Pub/Sub architecture, successfully piloting the solution with over 100 users.
Optimized API performance by integrating Redis caching, resulting in faster data access and a significant 60% reduction in latency from 2 seconds to 0.8 seconds.
Automated and streamlined CI/CD deployment pipelines using Cloud Build triggers, which reduced release time by 20% and enhanced development efficiency.
Education
University of Southern California
→
Master's
Computer Science
Courses
Analysis of Algorithms
Machine Learning
Natural Language Processing
Multimedia Systems Design
Indian Institute of Information Technology
→
Bachelor's
Computer Science
Courses
Data Structures and Algorithms
Information Retrieval
Deep Learning
Distributed Computing
Skills
Programming Languages
Python, Java, C/C++, SQL, JavaScript, TypeScript, Go.
Machine Learning
PyTorch, Scikit-Learn, Pandas, NumPy, Langchain, Hugging Face, Open CV.
Generative AI & Models
LLMs, Speech (TTS/ASR), Image (ViT), Multimodal Models, GPT-4V, Gemini.
Web Frameworks & Libraries
FastAPI, Django, React.js, Next.js, Node.js, D3.js.
Cloud & DevOps
AWS (EC2, S3), GCP, Docker, Kubernetes, Firebase, Apache Airflow.
Projects
Image Inpainting using Deep Learning
→
Summary
Explored and implemented advanced deep learning techniques for image inpainting and spatial reconstruction.
Publications
Published by
ACL 2025, SDP Workshop
Summary
Developed a multimodal Chain-of-Thought (CoT) reasoning pipeline for Scientific Visual QA, achieving high performance metrics and significantly accelerating inference speed.