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Arun chukkala

@arunchukkala

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AI/ML Engineer specializing in LLM technologies and MLOps.

United States

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What I'm looking for

I am looking for a role that fosters innovation, encourages collaboration, and provides opportunities for professional growth in AI and machine learning.

I am an AI/ML Engineer with over three years of experience in applying cutting-edge AI and machine learning technologies, particularly in the realms of fraud detection, finance, and search optimization. My recent work has focused on deploying large language models (LLMs) such as GPT-4 and Claude, where I have successfully improved accuracy by over 25% and reduced latency by 40% through effective model orchestration and deployment strategies.

Currently, I am working at Jefferies Group, where I deployed a customer lifetime value model that processes over 15 million records monthly, significantly boosting ROI. My expertise extends to integrating retrieval-augmented generation (RAG) systems and optimizing GPU inference, ensuring that the solutions I develop are not only innovative but also efficient and scalable. I am passionate about leveraging AI to create impactful solutions and continuously seek to enhance my skills in this rapidly evolving field.

Experience

Work history, roles, and key accomplishments

Current

AI/ML Engineer

Current

Jefferies Group

Mar 2024 - Present (1 year 2 months)

Deployed a customer lifetime value (CLV) model on SageMaker, significantly boosting ROI by 25%. Integrated a RAG system with LangChain and Pinecone for instant document retrieval with GPT-4o summaries, and replaced HuggingFace inference with vLLM and Triton, cutting latency by 60%. Automated evaluations and retraining using LangSmith and Weights & Biases, with CI/CD via GitHub Actions.

Sagemaker Lang Chain Pinecone GPT 4o Triton Langsmith Weights Biases GitHub Actions

Associate AI/ML Engineer

Experian

Jan 2021 - Dec 2022 (1 year 11 months)

Developed a fraud detection system using Isolation Forest and Autoencoders, which reduced false positives by 40%. Implemented real-time streaming with Kafka and Ray Serve, achieving inference SLAs under 200ms. Designed explainability dashboards in Power BI and maintained Azure ML pipelines.

Isolation Forest Kafka Power BI Machine Learning Fraud Detection Python

Education

Degrees, certifications, and relevant coursework

Lamar University

Master of Science, Computer Science

Conducted research focused on optimizing Large Language Model (LLM) performance, specifically in environments with resource constraints. This involved exploring various techniques to enhance efficiency and reduce computational overhead for LLMs.

Sri Indu Institute of Engineering & Technology

Bachelor of Technology, Computer Science

Studied core principles of computer science and engineering, covering fundamental concepts and practical applications. Gained a strong foundation in software development, algorithms, and data structures.