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Kollaikal Rupesh

@kollaikalrupesh

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ML Engineer and MSBA candidate passionate about impactful data solutions.

United States

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What I'm looking for

I seek a collaborative environment where I can leverage my ML skills to drive innovation and contribute to impactful projects.

I am an ML Engineer and MSBA candidate at UC Davis, dedicated to building production-grade systems that integrate large language models (LLMs) with forecasting models and scalable infrastructure. My experience includes deploying real-time pipelines using FastAPI, Docker, and Pinecone, which have significantly enhanced semantic search and intelligent automation capabilities. I thrive on bridging statistical modeling with practical engineering to create fast, modular, and measurable impacts in my projects.

Throughout my career, I have successfully delivered high-quality results, such as achieving 200ms latency across multiple client pipelines and improving semantic search accuracy by 25% through innovative solutions. My work at SocioSquares involved building async ML pipelines that reduced SEO data processing time by 45%, showcasing my ability to enhance system throughput and efficiency. I am passionate about leveraging my skills in AI/ML engineering, data engineering, and statistical modeling to drive impactful outcomes in various domains.

Experience

Work history, roles, and key accomplishments

Current

Machine Learning Engineer

Current

SocioSquares

Oct 2024 - Present (7 months)

Deployed FastAPI microservices in Docker for real-time SEO inference, achieving 200ms latency across 5 client pipelines. Created a Pinecone-based vector index with over 50K domain embeddings, improving semantic search accuracy by 25%. Built async ML pipelines integrated with LLM-based content workflows, reducing SEO data processing time by 45% and enhancing system throughput.

fastAPI Docker Pinecone LLM Semantic Search Asynchronous Programming SEO

Research Specialist I

Zoominfo

Oct 2023 - Present (1 year 7 months)

Delivered over 120K verified GTM signals with 98% accuracy, powering Copilot’s B2B forecasting and intelligence pipelines used by GTM strategy teams. Automated internal annotation workflows using a Python-based tool, reducing manual labeling time by 30% and enabling adoption across a 10+ member analyst team. Contributed 30% of production-grade data for a multi-million dollar ML model, enhancing le

Python Data Validation Machine Learning Lead Scoring Automation

Data & Impact Analyst

ORRC

Dec 2021 - Present (3 years 5 months)

Analyzed over 100K records using Pandas and ARIMA to optimize aid distribution, increasing resource efficiency by 35%. Built real-time Streamlit dashboards to monitor health, education, and employment KPIs, reducing reporting time by 20% and enabling data-backed decisions. Forecasted outreach needs using ARIMA and seasonal decomposition, improving planning accuracy for policy interventions.

Pandas Streamlit Data Analysis Time Series Analysis KPIs Forecasting