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Hi there! I’m Sai Dheeraj Mannarugudi, an AI/ML engineer with 2+ years of hands-on experience in LLMs, NLP, deep learning, and reinforcement learning. I enjoy designing agentic AI systems, including ASR/TTS and computer vision, and building end-to-end pipelines, prompts, RAG, and knowledge graphs. I deploy scalable models via MLOps on the cloud with a strong focus on safety, bias reduction, and reliable performance. I thrive in collaborative environments and love turning complex AI challenges into practical, ethical solutions.…Hi there! I’m Sai Dheeraj Mannarugudi, an AI/ML engineer with 2+ years of hands-on experience in LLMs, NLP, deep learning, and reinforcement learning. I enjoy designing agentic AI systems, including ASR/TTS and computer vision, and building end-to-end pipelines, prompts, RAG, and knowledge graphs. I deploy scalable models via MLOps on the cloud with a strong focus on safety, bias reduction, and reliable performance. I thrive in collaborative environments and love turning complex AI challenges into practical, ethical solutions.

MANNARUGUDI SAI DHEERAJ

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

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Hi there! I’m Sai Dheeraj Mannarugudi, an AI/ML engineer with 2+ years of hands-on experience in LLMs, NLP, deep learning, and reinforcement learning. I enjoy designing agentic AI systems, including ASR/TTS and computer vision, and building end-to-end pipelines, prompts, RAG, and knowledge graphs. I deploy scalable models via MLOps on the cloud with a strong focus on safety, bias reduction, and reliable performance. I thrive in collaborative environments and love turning complex AI challenges into practical, ethical solutions.…Hi there! I’m Sai Dheeraj Mannarugudi, an AI/ML engineer with 2+ years of hands-on experience in LLMs, NLP, deep learning, and reinforcement learning. I enjoy designing agentic AI systems, including ASR/TTS and computer vision, and building end-to-end pipelines, prompts, RAG, and knowledge graphs. I deploy scalable models via MLOps on the cloud with a strong focus on safety, bias reduction, and reliable performance. I thrive in collaborative environments and love turning complex AI challenges into practical, ethical solutions.

Available to hire

Hi there! I’m Sai Dheeraj Mannarugudi, an AI/ML engineer with 2+ years of hands-on experience in LLMs, NLP, deep learning, and reinforcement learning. I enjoy designing agentic AI systems, including ASR/TTS and computer vision, and building end-to-end pipelines, prompts, RAG, and knowledge graphs.

I deploy scalable models via MLOps on the cloud with a strong focus on safety, bias reduction, and reliable performance. I thrive in collaborative environments and love turning complex AI challenges into practical, ethical solutions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Work Experience

AI/ML Computational Science Associate at Accenture Solutions Pvt. Ltd.

July 1, 2024 - Present

Engineered agentic AI systems leveraging NLP, prompt design, and reinforcement learning; delivered scalable architectures with API and knowledge graph integrations. Conducted threat modeling and security design reviews for AI/ML services, identifying attack vectors and mitigating risks across APIs, data pipelines, and inference layers. Designed and deployed LLM agents supporting multi-turn dialogue, decision-making, and contextual reasoning. Integrated agents with CI/CD and testing platforms. Fine-tuned LLMs for domain-specific tasks; created AI-centric UI patterns in React including streaming LLM responses, feedback capture, and human-in-the-loop validation. Built end-to-end pipelines from data preprocessing through model training, evaluation, and deployment. Developed scalable frameworks for NLP and ASR/TTS; scaled to 2,500+ requests/second with 99.3% uptime. Applied prompt engineering and fine-tuning to enhance model responses, achieving a 34% accuracy improvement and reducing avera

Teaching Assistant at Vignan's Foundation for Science Technology and Research, ULEARN

August 1, 2023 - June 30, 2024

Provided 1:1 mentoring to students, resolving queries and clarifying doubts to enhance comprehension, increasing satisfaction by 42%. Facilitated hands-on sessions with OpenCV, guiding students through practical implementations; improved lab completion rate by 54%. Assisted students in implementing efficient algorithms, emphasizing problem-solving skills and clean coding practices. Optimized tutoring workflow by batching Q&A sessions, cutting average response time from 6 minutes to 2 minutes, boosting student throughput by 67%. Created reusable teaching aids, code templates, and helper scripts to scale mentoring across cohorts, reducing instructor handoffs errors by 40% while maintaining session quality. Implemented lightweight validation checks for student submissions, lowering rework cases from 18 to 5 per term (72% reduction).