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Software engineer specializing in AI/ML infrastructure with 3+ years of experience building scalable AI platforms, distributed ML systems, and cloud-native infrastructure for FinTech and enterprise applications. I design production-grade RAG pipelines, LLM orchestration and agent workflows, and real-time data systems using Python, AWS, Kafka, Spark, and LangChain. I build reusable AI infrastructure and observability tooling to support secure, reliable, high-performance AI applications at scale. I’m experienced in MLOps, distributed systems, CI/CD automation, and optimizing cloud infrastructure for AI workloads.…Software engineer specializing in AI/ML infrastructure with 3+ years of experience building scalable AI platforms, distributed ML systems, and cloud-native infrastructure for FinTech and enterprise applications. I design production-grade RAG pipelines, LLM orchestration and agent workflows, and real-time data systems using Python, AWS, Kafka, Spark, and LangChain. I build reusable AI infrastructure and observability tooling to support secure, reliable, high-performance AI applications at scale. I’m experienced in MLOps, distributed systems, CI/CD automation, and optimizing cloud infrastructure for AI workloads.

Chandana Talla

AI Engineer, Data Scientist, AI Developer, +6

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Software engineer specializing in AI/ML infrastructure with 3+ years of experience building scalable AI platforms, distributed ML systems, and cloud-native infrastructure for FinTech and enterprise applications. I design production-grade RAG pipelines, LLM orchestration and agent workflows, and real-time data systems using Python, AWS, Kafka, Spark, and LangChain. I build reusable AI infrastructure and observability tooling to support secure, reliable, high-performance AI applications at scale. I’m experienced in MLOps, distributed systems, CI/CD automation, and optimizing cloud infrastructure for AI workloads.…Software engineer specializing in AI/ML infrastructure with 3+ years of experience building scalable AI platforms, distributed ML systems, and cloud-native infrastructure for FinTech and enterprise applications. I design production-grade RAG pipelines, LLM orchestration and agent workflows, and real-time data systems using Python, AWS, Kafka, Spark, and LangChain. I build reusable AI infrastructure and observability tooling to support secure, reliable, high-performance AI applications at scale. I’m experienced in MLOps, distributed systems, CI/CD automation, and optimizing cloud infrastructure for AI workloads.

Available to hire

Software engineer specializing in AI/ML infrastructure with 3+ years of experience building scalable AI platforms, distributed ML systems, and cloud-native infrastructure for FinTech and enterprise applications. I design production-grade RAG pipelines, LLM orchestration and agent workflows, and real-time data systems using Python, AWS, Kafka, Spark, and LangChain.

I build reusable AI infrastructure and observability tooling to support secure, reliable, high-performance AI applications at scale. I’m experienced in MLOps, distributed systems, CI/CD automation, and optimizing cloud infrastructure for AI workloads.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Beginner

Beginner

Language

English

Fluent

Work Experience

AI/ML Engineer at Citigroup

January 1, 2025 - Present

AI/ML Engineer at Citigroup: Architected a secure Retrieval-Augmented Generation (RAG) system using Llama 3 and LangChain to automate financial document summarization, reducing manual review time by 65% and improving data retrieval accuracy by 28% for internal audit teams. Engineered high-frequency fraud detection with XGBoost and PyTorch on AWS SageMaker, processing 1TB+ daily and improving false-positive rate by 18%, mitigating approximately $1.2M in annual losses. Implemented a fully automated CI/CD pipeline with GitHub Actions, Docker, and Kubernetes to retrain and deploy models, reducing deployment cycles from 3 days to 4 hours while maintaining 99.9% API uptime. Built real-time ingestion pipelines with Apache Kafka and Spark Structured Streaming for sub-second latency (<200ms) in trading signals. Migrated on-prem ETL to serverless AWS Glue and Snowflake, cutting query times by 45% and cloud costs by 30%. Fine-tuned BERT/RoBERTa to analyze sentiment across multi-channel support ti

Machine Learning Engineer at Space Infolab

January 1, 2021 - August 1, 2023

Machine Learning Engineer at Space Infolab: Built an automated quality control system using OpenCV and CNNs (ResNet50) achieving 94% defect detection accuracy, reducing manual inspection overhead by 40%. Developed churn prediction engine using Random Forest with 89% precision, enabling targeted retention strategies. Implemented RESTful APIs with FastAPI and Flask serving ML models to the front-end, handling 5,000+ requests per minute with asynchronous processing and load balancing. Engineered scalable data preprocessing pipelines using PySpark on Hadoop for 500GB+ raw data, improving dataset quality scores by 35% for downstream analytics. Designed a collaborative filtering recommender using Matrix Factorization to personalize content, increasing session duration by 22%. Optimized complex SQL queries in PostgreSQL and MongoDB with indexing, achieving ~3x faster reporting. Conducted rigorous A/B testing to validate feature improvements with statistical significance and supported data-dri