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I’m an AI developer with 4+ years of experience building enterprise-grade, cloud-native applications and data-driven systems. I specialize in backend development, APIs, and distributed architectures, with hands-on expertise in end-to-end ML and Generative AI solutions in production.\n\nI’ve worked with LLMs, NLP, deep learning, and MLOps to design scalable AI architectures and automated workflows. I excel at integrating intelligent automation into robust software systems and deploying models on cloud platforms with real-time monitoring and reliability.…I’m an AI developer with 4+ years of experience building enterprise-grade, cloud-native applications and data-driven systems. I specialize in backend development, APIs, and distributed architectures, with hands-on expertise in end-to-end ML and Generative AI solutions in production.\n\nI’ve worked with LLMs, NLP, deep learning, and MLOps to design scalable AI architectures and automated workflows. I excel at integrating intelligent automation into robust software systems and deploying models on cloud platforms with real-time monitoring and reliability.

Anirudh Gopal

AI Developer, Data Scientist, Full Stack Developer, +2

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I’m an AI developer with 4+ years of experience building enterprise-grade, cloud-native applications and data-driven systems. I specialize in backend development, APIs, and distributed architectures, with hands-on expertise in end-to-end ML and Generative AI solutions in production.\n\nI’ve worked with LLMs, NLP, deep learning, and MLOps to design scalable AI architectures and automated workflows. I excel at integrating intelligent automation into robust software systems and deploying models on cloud platforms with real-time monitoring and reliability.…I’m an AI developer with 4+ years of experience building enterprise-grade, cloud-native applications and data-driven systems. I specialize in backend development, APIs, and distributed architectures, with hands-on expertise in end-to-end ML and Generative AI solutions in production.\n\nI’ve worked with LLMs, NLP, deep learning, and MLOps to design scalable AI architectures and automated workflows. I excel at integrating intelligent automation into robust software systems and deploying models on cloud platforms with real-time monitoring and reliability.

Available to hire

I’m an AI developer with 4+ years of experience building enterprise-grade, cloud-native applications and data-driven systems. I specialize in backend development, APIs, and distributed architectures, with hands-on expertise in end-to-end ML and Generative AI solutions in production.\n\nI’ve worked with LLMs, NLP, deep learning, and MLOps to design scalable AI architectures and automated workflows. I excel at integrating intelligent automation into robust software systems and deploying models on cloud platforms with real-time monitoring and reliability.

Skills

Experience Level

Expert

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Language

English

Fluent

Work Experience

AI Developer at Morgan Stanley

January 1, 2025 - Present

Engineered and deployed production-grade Generative AI platforms, integrating LLMs into resilient backend architectures; fine-tuned open-source LLMs on proprietary corpora, enhancing classification and summarization by 29%; optimized inference latency by 28% via mixed-precision quantization and batching; automated model retraining and CI/CD pipelines with MLflow and monitoring frameworks; designed advanced data preprocessing and feature engineering for high-dimensional structured datasets; deployed ML models on AWS SageMaker with real-time monitoring and fault tolerance; accelerated ETL processing efficiency by 31% through pipeline restructuring and parallelization; integrated advanced prompt engineering to improve response consistency and domain-specific understanding; conducted rigorous model evaluation and hyperparameter tuning to improve accuracy and reliability; developed Retrieval-Augmented Generation (RAG) knowledge assistants increasing contextual relevance by 33%.

Software Engineer at Borland Software

August 1, 2020 - June 1, 2023

Engineered and deployed ML models for telecom network traffic forecasting, increasing prediction accuracy by 34%; advanced data preprocessing, feature engineering, and hyperparameter tuning using Python and Scikit-learn pipelines; designed and automated scalable ETL pipelines, optimizing SQL workflows and reducing data processing time by 29%; developed robust Python and Linux automation scripts to streamline workflows and generate analytic reports for stakeholders; implemented responsive web interfaces and RESTful APIs in Java, enhancing backend system performance by 36%; collaborated with cross-functional teams to deploy ML-driven solutions; leveraged anomaly detection and predictive modeling to identify network congestion and minimize downtime; applied explainable AI and model interpretability to validate predictions and improve transparency; continuously monitored and fine-tuned deployed models for sustained performance and reliability; conducted comprehensive Exploratory Data Analy