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Machine Learning Engineer with 5+ years of experience building scalable, production-grade AI systems, including LLM-powered recommendation and multilingual NLP platforms across high-impact environments. Proven track record of improving retrieval diversity, engagement, and latency using generative AI techniques, transformer architectures, and ANN-based semantic search at scale. Strong expertise in end-to-end ML and GenAI systems, from data pipelines and model training to real-time inference and cloud-native deployment on AWS infrastructure. Adept at designing distributed, high-throughput systems that combine AI/ML with robust backend engineering to deliver measurable business impact.…Machine Learning Engineer with 5+ years of experience building scalable, production-grade AI systems, including LLM-powered recommendation and multilingual NLP platforms across high-impact environments. Proven track record of improving retrieval diversity, engagement, and latency using generative AI techniques, transformer architectures, and ANN-based semantic search at scale. Strong expertise in end-to-end ML and GenAI systems, from data pipelines and model training to real-time inference and cloud-native deployment on AWS infrastructure. Adept at designing distributed, high-throughput systems that combine AI/ML with robust backend engineering to deliver measurable business impact.

Sai Chandra Palle

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

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Machine Learning Engineer with 5+ years of experience building scalable, production-grade AI systems, including LLM-powered recommendation and multilingual NLP platforms across high-impact environments. Proven track record of improving retrieval diversity, engagement, and latency using generative AI techniques, transformer architectures, and ANN-based semantic search at scale. Strong expertise in end-to-end ML and GenAI systems, from data pipelines and model training to real-time inference and cloud-native deployment on AWS infrastructure. Adept at designing distributed, high-throughput systems that combine AI/ML with robust backend engineering to deliver measurable business impact.…Machine Learning Engineer with 5+ years of experience building scalable, production-grade AI systems, including LLM-powered recommendation and multilingual NLP platforms across high-impact environments. Proven track record of improving retrieval diversity, engagement, and latency using generative AI techniques, transformer architectures, and ANN-based semantic search at scale. Strong expertise in end-to-end ML and GenAI systems, from data pipelines and model training to real-time inference and cloud-native deployment on AWS infrastructure. Adept at designing distributed, high-throughput systems that combine AI/ML with robust backend engineering to deliver measurable business impact.

Available to hire

Machine Learning Engineer with 5+ years of experience building scalable, production-grade AI systems, including LLM-powered recommendation and multilingual NLP platforms across high-impact environments. Proven track record of improving retrieval diversity, engagement, and latency using generative AI techniques, transformer architectures, and ANN-based semantic search at scale.

Strong expertise in end-to-end ML and GenAI systems, from data pipelines and model training to real-time inference and cloud-native deployment on AWS infrastructure. Adept at designing distributed, high-throughput systems that combine AI/ML with robust backend engineering to deliver measurable business impact.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Machine Learning Engineer at Pinterest

August 1, 2024 - Present

Led LLM-powered generative retrieval and semantic ranking initiatives to boost diversity and engagement; implemented dense embedding pipelines for semantic search and RAG-based retrieval; developed ANN-based candidate generation with Faiss (IVF-HNSW) for scalable, high-quality recommendations; designed distributed data pipelines on AWS EMR with Spark; built scalable multi-stage inference workflows and microservice-based ML architectures (TorchScript deployment) to improve throughput and latency; leveraged AWS S3 and Iceberg on S3 for feature storage and experiment tracking.

Machine Learning Engineer at Amazon India

January 1, 2020 - July 1, 2023

Enhanced multilingual query understanding by 34% for code-mixed inputs; reduced API latency by 29% via optimized real-time inference pipelines and caching; increased data processing efficiency by 38% with scalable ETL on AWS Glue and S3 for multilingual datasets. Built and fine-tuned transformer-based models (XLM-R, mT5) for multilingual NLP tasks, deployed on AWS (EC2, SageMaker) with monitoring (CloudWatch) and robust backend services.