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Hi, I’m Indra Reddy, an AI/ML Engineer and Data Scientist with 4+ years of experience turning complex data into tangible business value across financial services and SaaS. I’ve worked on fine-tuning LLMs, RAG pipelines, and real-time fraud analytics to boost model precision and drive revenue. I build scalable, explainable ML systems with strong MLOps, observability, and secure governance. My toolkit includes Python, PyTorch, TensorFlow, SQL, and vector stores like FAISS, Pinecone, and Milvus, deployed on AWS, Kubernetes, and cloud-native infra. I thrive on turning research into deployable solutions that meet regulatory expectations.…Hi, I’m Indra Reddy, an AI/ML Engineer and Data Scientist with 4+ years of experience turning complex data into tangible business value across financial services and SaaS. I’ve worked on fine-tuning LLMs, RAG pipelines, and real-time fraud analytics to boost model precision and drive revenue. I build scalable, explainable ML systems with strong MLOps, observability, and secure governance. My toolkit includes Python, PyTorch, TensorFlow, SQL, and vector stores like FAISS, Pinecone, and Milvus, deployed on AWS, Kubernetes, and cloud-native infra. I thrive on turning research into deployable solutions that meet regulatory expectations.

Indra Reddy

AI Engineer, Data Scientist, Developer, +2

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Hi, I’m Indra Reddy, an AI/ML Engineer and Data Scientist with 4+ years of experience turning complex data into tangible business value across financial services and SaaS. I’ve worked on fine-tuning LLMs, RAG pipelines, and real-time fraud analytics to boost model precision and drive revenue. I build scalable, explainable ML systems with strong MLOps, observability, and secure governance. My toolkit includes Python, PyTorch, TensorFlow, SQL, and vector stores like FAISS, Pinecone, and Milvus, deployed on AWS, Kubernetes, and cloud-native infra. I thrive on turning research into deployable solutions that meet regulatory expectations.…Hi, I’m Indra Reddy, an AI/ML Engineer and Data Scientist with 4+ years of experience turning complex data into tangible business value across financial services and SaaS. I’ve worked on fine-tuning LLMs, RAG pipelines, and real-time fraud analytics to boost model precision and drive revenue. I build scalable, explainable ML systems with strong MLOps, observability, and secure governance. My toolkit includes Python, PyTorch, TensorFlow, SQL, and vector stores like FAISS, Pinecone, and Milvus, deployed on AWS, Kubernetes, and cloud-native infra. I thrive on turning research into deployable solutions that meet regulatory expectations.

Available to hire

Hi, I’m Indra Reddy, an AI/ML Engineer and Data Scientist with 4+ years of experience turning complex data into tangible business value across financial services and SaaS. I’ve worked on fine-tuning LLMs, RAG pipelines, and real-time fraud analytics to boost model precision and drive revenue.

I build scalable, explainable ML systems with strong MLOps, observability, and secure governance. My toolkit includes Python, PyTorch, TensorFlow, SQL, and vector stores like FAISS, Pinecone, and Milvus, deployed on AWS, Kubernetes, and cloud-native infra. I thrive on turning research into deployable solutions that meet regulatory expectations.

Skills

Experience Level

Expert

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Expert

Expert

Expert

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Expert

Expert

Expert

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Expert

Language

English

Fluent

Work Experience

AI/ML Engineer at State Street

September 1, 2024 - Present

Orchestrated large-scale LLM fine-tuning (GPT, LLaMA, Claude, NVIDIA NeMo) on AWS SageMaker and DGX Cloud; improved response precision by 31% and reduced latency through quantization. Spearheaded real-time fraud analytics using Kafka, Spark Streaming, Snowflake, and Redis; deployed drift-aware models via Kubeflow pipelines, reducing false positives by 27%. Implemented GPU-optimized inference services with Kubernetes (EKS), Docker, and Triton Inference Server; achieved 38% cost savings and stable auto-scaling under peak workloads. Championed observability with Prometheus, Grafana, and ELK Stack; automated retraining triggers and explainability dashboards aligned with U.S. regulatory standards, improving governance metrics by 33%. Architected end-to-end RAG pipelines using Hugging Face transformers, FAISS, Pinecone, and Milvus for semantic search across financial documents, reducing research turnaround by 42% and influencing decisions impacting $178M in managed assets.

Data Scientist at Freshworks Inc

March 1, 2020 - November 1, 2022

Directed NLP-driven recommendation systems leveraging Python, XGBoost, and embedding-based retrieval to boost customer engagement by 29% and renewals by 17% across SaaS products. Built anomaly detection models identifying revenue leakage (~$2.4M/year) and implemented automated MLOps with MLflow, Airflow, and AWS (S3, Redshift) to standardize experiments and shorten deployment cycles by 46%. Engineered streaming ingestion with Kafka and Spark Streaming enabling near real-time analytics for support insights, reducing resolution time by 36%. Advanced explainable AI dashboards with dbt, MongoDB, and Grafana to improve transparency and trust in AI-driven insights by 42%.