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I'm an AI/ML Engineer with around four years of experience across finance, retail, and healthcare. I’m proficient in Python, TensorFlow, PyTorch, XGBoost, LLMs, Hugging Face Transformers, LangChain, RAG pipelines, Pinecone, SQL, and Power BI, with a strong track record of turning data into actionable enterprise insights. I design and deploy scalable AI solutions that reduce analyst turnaround times and generate measurable savings, such as $70,000 in annual cost savings from AI/ML deployments. I enjoy building end-to-end pipelines, tuning LLMs (LoRA/PEFT/adapters), and delivering domain-specific intelligence that informs strategic decisions.…I'm an AI/ML Engineer with around four years of experience across finance, retail, and healthcare. I’m proficient in Python, TensorFlow, PyTorch, XGBoost, LLMs, Hugging Face Transformers, LangChain, RAG pipelines, Pinecone, SQL, and Power BI, with a strong track record of turning data into actionable enterprise insights. I design and deploy scalable AI solutions that reduce analyst turnaround times and generate measurable savings, such as $70,000 in annual cost savings from AI/ML deployments. I enjoy building end-to-end pipelines, tuning LLMs (LoRA/PEFT/adapters), and delivering domain-specific intelligence that informs strategic decisions.

Jayesh Locharla

AI Engineer, Data Scientist, Web Developer, +3

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I'm an AI/ML Engineer with around four years of experience across finance, retail, and healthcare. I’m proficient in Python, TensorFlow, PyTorch, XGBoost, LLMs, Hugging Face Transformers, LangChain, RAG pipelines, Pinecone, SQL, and Power BI, with a strong track record of turning data into actionable enterprise insights. I design and deploy scalable AI solutions that reduce analyst turnaround times and generate measurable savings, such as $70,000 in annual cost savings from AI/ML deployments. I enjoy building end-to-end pipelines, tuning LLMs (LoRA/PEFT/adapters), and delivering domain-specific intelligence that informs strategic decisions.…I'm an AI/ML Engineer with around four years of experience across finance, retail, and healthcare. I’m proficient in Python, TensorFlow, PyTorch, XGBoost, LLMs, Hugging Face Transformers, LangChain, RAG pipelines, Pinecone, SQL, and Power BI, with a strong track record of turning data into actionable enterprise insights. I design and deploy scalable AI solutions that reduce analyst turnaround times and generate measurable savings, such as $70,000 in annual cost savings from AI/ML deployments. I enjoy building end-to-end pipelines, tuning LLMs (LoRA/PEFT/adapters), and delivering domain-specific intelligence that informs strategic decisions.

Available to hire

I’m an AI/ML Engineer with around four years of experience across finance, retail, and healthcare. I’m proficient in Python, TensorFlow, PyTorch, XGBoost, LLMs, Hugging Face Transformers, LangChain, RAG pipelines, Pinecone, SQL, and Power BI, with a strong track record of turning data into actionable enterprise insights.

I design and deploy scalable AI solutions that reduce analyst turnaround times and generate measurable savings, such as $70,000 in annual cost savings from AI/ML deployments. I enjoy building end-to-end pipelines, tuning LLMs (LoRA/PEFT/adapters), and delivering domain-specific intelligence that informs strategic decisions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

AI/ML Engineer at Walmart

September 1, 2024 - Present

Designed and deployed Generative AI solutions using LLMs (LLaMA, GPT-family) to automate document understanding for merchandising, compliance, and supplier operations, accelerating analyst processing from 4–5 days to same-day. Programmed RAG pipelines with Pinecone for semantic search across enterprise knowledge sources, reducing information retrieval latency by 45% and boosting AI tool adoption. Built LangChain-based orchestration workflows integrating LLMs with internal SQL systems, APIs, and governed data assets to standardize AI-assisted workflows. Trained PyTorch-based recommendation and ranking models for product discovery, achieving real-time performance with reduced inference latency by 20 ms per request. Established prompt engineering standards and reusable prompt libraries, cutting rework and manual review while delivering about $70,000 in annual savings. Implemented prompt tuning/LLM fine-tuning (LoRA/PEFT/adapters) for domain-specific merchandising and compliance tasks, i

Machine Learning Scientist at Goldman Sachs

January 1, 2021 - July 1, 2023

Improved credit risk assessment by 18% by building TensorFlow and XGBoost models on 9M historical loans and transactions, enabling risk teams to prioritize high-risk accounts and reduce manual review cycles. Reduced fraud investigation latency by 45 minutes per batch by implementing Isolation Forest and autoencoder-based anomaly detection on 1,500+ suspicious transactions monthly. Increased portfolio forecasting accuracy by 22% using LSTM and ARIMA models for market exposure and trading volume prediction, supporting more precise hedging strategies for trading desks. Automated compliance document analysis, cutting review time from 3 hours to 50 minutes per report, by deploying NLP pipelines with Hugging Face Transformers and spaCy to extract actionable insights from audit logs, emails, and trade notes. Applied model interpretability frameworks with SHAP, LIME, and PCA, highlighting top predictors across risk models and ensuring audit-ready transparency for regulatory reporting. Rolled o