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I am a Machine Learning Engineer with 5+ years of experience building scalable Gen AI systems, distributed platforms, and production AI infrastructure across mobility and enterprise environments. I specialize in high-throughput inference services, hybrid-search RAG pipelines, real-time Kafka streaming systems, and ML feature engineering using Python, Java, Spark, FastAPI, and Kubernetes. I have hands-on experience with low-latency AI serving, vector retrieval workflows, automated evaluation pipelines, and scalable back-end systems that raise model accuracy, platform scalability, and cloud efficiency.…I am a Machine Learning Engineer with 5+ years of experience building scalable Gen AI systems, distributed platforms, and production AI infrastructure across mobility and enterprise environments. I specialize in high-throughput inference services, hybrid-search RAG pipelines, real-time Kafka streaming systems, and ML feature engineering using Python, Java, Spark, FastAPI, and Kubernetes. I have hands-on experience with low-latency AI serving, vector retrieval workflows, automated evaluation pipelines, and scalable back-end systems that raise model accuracy, platform scalability, and cloud efficiency.

Sai Anuhya Bandi

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

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I am a Machine Learning Engineer with 5+ years of experience building scalable Gen AI systems, distributed platforms, and production AI infrastructure across mobility and enterprise environments. I specialize in high-throughput inference services, hybrid-search RAG pipelines, real-time Kafka streaming systems, and ML feature engineering using Python, Java, Spark, FastAPI, and Kubernetes. I have hands-on experience with low-latency AI serving, vector retrieval workflows, automated evaluation pipelines, and scalable back-end systems that raise model accuracy, platform scalability, and cloud efficiency.…I am a Machine Learning Engineer with 5+ years of experience building scalable Gen AI systems, distributed platforms, and production AI infrastructure across mobility and enterprise environments. I specialize in high-throughput inference services, hybrid-search RAG pipelines, real-time Kafka streaming systems, and ML feature engineering using Python, Java, Spark, FastAPI, and Kubernetes. I have hands-on experience with low-latency AI serving, vector retrieval workflows, automated evaluation pipelines, and scalable back-end systems that raise model accuracy, platform scalability, and cloud efficiency.

Available to hire

I am a Machine Learning Engineer with 5+ years of experience building scalable Gen AI systems, distributed platforms, and production AI infrastructure across mobility and enterprise environments.
I specialize in high-throughput inference services, hybrid-search RAG pipelines, real-time Kafka streaming systems, and ML feature engineering using Python, Java, Spark, FastAPI, and Kubernetes. I have hands-on experience with low-latency AI serving, vector retrieval workflows, automated evaluation pipelines, and scalable back-end systems that raise model accuracy, platform scalability, and cloud efficiency.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

Javanese

Advanced

Work Experience

Gen AI Engineer at Uber

June 1, 2025 - Present

Built a production-grade hybrid-search RAG platform using LangChain and FAISS to index 2M+ records, implementing semantic chunking strategies that reduced factual drift across 12 customer-support intent classes. Scaled asynchronous FastAPI inference services processing 15K+ daily requests with adaptive batching, Redis semantic caching, and intelligent fallback routing, reducing API token costs and intercepting 14 edge-case query failures. Owned real-time Kafka-based feature ingestion pipelines streaming 55K+ trip events hourly, collaborating with ML and platform teams to enable low-latency contextual data delivery for production inference systems. Automated LLM evaluation pipelines using PyTest, ground-truth scoring, and AWS Pinecone validation checks across 4M+ vector embeddings, strengthening retrieval accuracy and continuous model validation workflows.

Software Engineer at TCS

August 1, 2021 - August 1, 2023

Redesigned distributed Apache Spark ETL pipelines processing 1.2 TB of data daily, optimizing partition strategies and broadcast joins to reduce batch execution time by 2.7 hours and increase large-scale processing throughput. Developed scalable Spring Boot microservices handling 10K+ daily API requests using concurrent thread pools and HikariCP pooling, eliminating recurring integration failures across 7 production services. Coordinated production Apache Airflow DAGs containing 320 daily workflows, implementing retry policies and dependency management to reduce weekly job failures from 18 to 3 across shared data pipelines. Standardized ML feature engineering pipelines using Python and Pandas to process 240+ training metrics, accelerating model preparation cycle by 95 minutes while ensuring consistent datasets for ML workflows.

Software Engineer at Robosoft Technologies

June 1, 2019 - July 1, 2021

Built modular RESTful APIs using Node.js and Express for 9 enterprise applications handling 6K+ daily requests, reducing API response latency by 180ms and improving downstream application performance across production systems. Optimized production SQL database schemas and automated archival workflows for high-volume transactional systems, improving query execution efficiency while reducing infrastructure overhead and recurring cloud storage costs. Strengthened API security across 12 production endpoints by implementing centralized JWT and OAuth 2 authentication, enabling secure service-to-service communication and improving production compliance standards. Streamlined Python-based data workflows to validate and process 420K+ operational records daily, increasing data accuracy and eliminating manual verification tasks that consumed 6 hours weekly.