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Hi, I’m Vikas Reddy, a Machine Learning Engineer with 4+ years of experience building scalable AI/ML and Generative AI systems. I specialize in LLMs, RAG pipelines, and multi-agent architectures, delivering AI solutions used by 3,000+ users and continuously improving model accuracy while reducing latency. I have strong expertise in Python, FastAPI, Kubernetes, and modern AI frameworks, with hands-on experience in end-to-end ML pipelines and real-time systems. I’m known for driving business outcomes through scalable system design and cross-functional collaboration.…Hi, I’m Vikas Reddy, a Machine Learning Engineer with 4+ years of experience building scalable AI/ML and Generative AI systems. I specialize in LLMs, RAG pipelines, and multi-agent architectures, delivering AI solutions used by 3,000+ users and continuously improving model accuracy while reducing latency. I have strong expertise in Python, FastAPI, Kubernetes, and modern AI frameworks, with hands-on experience in end-to-end ML pipelines and real-time systems. I’m known for driving business outcomes through scalable system design and cross-functional collaboration.

Vikas Reddy

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

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Hi, I’m Vikas Reddy, a Machine Learning Engineer with 4+ years of experience building scalable AI/ML and Generative AI systems. I specialize in LLMs, RAG pipelines, and multi-agent architectures, delivering AI solutions used by 3,000+ users and continuously improving model accuracy while reducing latency. I have strong expertise in Python, FastAPI, Kubernetes, and modern AI frameworks, with hands-on experience in end-to-end ML pipelines and real-time systems. I’m known for driving business outcomes through scalable system design and cross-functional collaboration.…Hi, I’m Vikas Reddy, a Machine Learning Engineer with 4+ years of experience building scalable AI/ML and Generative AI systems. I specialize in LLMs, RAG pipelines, and multi-agent architectures, delivering AI solutions used by 3,000+ users and continuously improving model accuracy while reducing latency. I have strong expertise in Python, FastAPI, Kubernetes, and modern AI frameworks, with hands-on experience in end-to-end ML pipelines and real-time systems. I’m known for driving business outcomes through scalable system design and cross-functional collaboration.

Available to hire

Hi, I’m Vikas Reddy, a Machine Learning Engineer with 4+ years of experience building scalable AI/ML and Generative AI systems. I specialize in LLMs, RAG pipelines, and multi-agent architectures, delivering AI solutions used by 3,000+ users and continuously improving model accuracy while reducing latency.

I have strong expertise in Python, FastAPI, Kubernetes, and modern AI frameworks, with hands-on experience in end-to-end ML pipelines and real-time systems. I’m known for driving business outcomes through scalable system design and cross-functional collaboration.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

AI/ML Engineer at Microsoft

May 1, 2024 - Present

Led the development of multi-agent AI orchestration pipelines, enabling autonomous task execution across enterprise systems and handling 1M+ workflows monthly for 3,000+ users. Implemented LLM-based RAG pipelines with embeddings, vector search, and reranking to improve response accuracy by 30% and reduce hallucinations by 25% across 100M+ monthly queries. Optimized inference latency to 900ms p95 and boosted throughput to 3K+ tokens/sec via dynamic batching, KV caching, and distributed serving. Built and deployed scalable microservices with Python, FastAPI, Kubernetes on Hyperscale Private Cloud, and integrated with Azure Logic Apps and enterprise systems. Implemented AI observability (Prometheus, Grafana) and CI/CD for secure, scalable delivery.

Machine Learning Engineer at Accenture

January 1, 2021 - July 1, 2023

Built LLM-powered conversational AI pipelines for intent classification and entity extraction, enabling automated customer support workflows used by 3,000+ users handling 500K+ queries monthly. Improved intent classification accuracy by 32% and reduced fallback rate by 28% by fine-tuning transformer models and optimizing training datasets using Python, Hugging Face, and NLP preprocessing pipelines. Developed and deployed LLM-enhanced dialogue management systems with Python and Azure Bot Framework, enabling multi-turn conversations and improving response latency by 25% while enhancing user satisfaction. Engineered backend APIs, data pipelines with Airflow and PySpark, and MLOps pipelines with MLflow, Docker, and CI/CD, enabling automated training, deployment, and monitoring across scalable enterprise AI environments. Deployed AI services on AWS and integrated with enterprise platforms across CRM, ERP, and backend systems.