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I am a Machine Learning Engineer with 4+ years of experience building and deploying production-scale AI systems across GenAI, NLP, and predictive analytics. I have hands-on expertise in RAG pipelines, LLM fine-tuning, and inference optimization, with production experience on large-scale infrastructure serving 50M+ daily queries at Meta. I am proficient in PyTorch, LangChain, LlamaIndex, vLLM, FastAPI, AWS, and distributed computing frameworks like Ray and PySpark. I have a proven track record of delivering measurable business impact, including reducing model serving latency by 2x and contributing to $4.2M+ in client revenue gains across retail and manufacturing.…I am a Machine Learning Engineer with 4+ years of experience building and deploying production-scale AI systems across GenAI, NLP, and predictive analytics. I have hands-on expertise in RAG pipelines, LLM fine-tuning, and inference optimization, with production experience on large-scale infrastructure serving 50M+ daily queries at Meta. I am proficient in PyTorch, LangChain, LlamaIndex, vLLM, FastAPI, AWS, and distributed computing frameworks like Ray and PySpark. I have a proven track record of delivering measurable business impact, including reducing model serving latency by 2x and contributing to $4.2M+ in client revenue gains across retail and manufacturing.

Dheeraja Kuruba

AI Engineer, Data Scientist, AI Developer, +2

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I am a Machine Learning Engineer with 4+ years of experience building and deploying production-scale AI systems across GenAI, NLP, and predictive analytics. I have hands-on expertise in RAG pipelines, LLM fine-tuning, and inference optimization, with production experience on large-scale infrastructure serving 50M+ daily queries at Meta. I am proficient in PyTorch, LangChain, LlamaIndex, vLLM, FastAPI, AWS, and distributed computing frameworks like Ray and PySpark. I have a proven track record of delivering measurable business impact, including reducing model serving latency by 2x and contributing to $4.2M+ in client revenue gains across retail and manufacturing.…I am a Machine Learning Engineer with 4+ years of experience building and deploying production-scale AI systems across GenAI, NLP, and predictive analytics. I have hands-on expertise in RAG pipelines, LLM fine-tuning, and inference optimization, with production experience on large-scale infrastructure serving 50M+ daily queries at Meta. I am proficient in PyTorch, LangChain, LlamaIndex, vLLM, FastAPI, AWS, and distributed computing frameworks like Ray and PySpark. I have a proven track record of delivering measurable business impact, including reducing model serving latency by 2x and contributing to $4.2M+ in client revenue gains across retail and manufacturing.

Available to hire

I am a Machine Learning Engineer with 4+ years of experience building and deploying production-scale AI systems across GenAI, NLP, and predictive analytics. I have hands-on expertise in RAG pipelines, LLM fine-tuning, and inference optimization, with production experience on large-scale infrastructure serving 50M+ daily queries at Meta.

I am proficient in PyTorch, LangChain, LlamaIndex, vLLM, FastAPI, AWS, and distributed computing frameworks like Ray and PySpark. I have a proven track record of delivering measurable business impact, including reducing model serving latency by 2x and contributing to $4.2M+ in client revenue gains across retail and manufacturing.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Language

English

Advanced

Work Experience

Machine Learning Engineer at Meta

January 1, 2025 - Present

Built and deployed production-scale RAG pipeline using LlamaIndex, LangChain, FAISS, and Pinecone over 2M+ documents, improving answer precision by 18% and reducing hallucination rates by 12% across 50M+ daily content moderation queries. Developed automated benchmarking framework evaluating 50+ fine-tuned LLM variants across accuracy, latency, and safety metrics, reducing model selection cycles from 3 weeks to 2 days. Optimized LLM inference workloads with vLLM, PyTorch, INT8 quantization, and dynamic batching on an 8×A100 GPU cluster, achieving P99 latency of 48ms at 10K+ concurrent requests and 2x throughput improvement. Built scalable FastAPI and gRPC model serving APIs handling 50K+ requests/minute at 99.99% uptime, supporting real-time and batch inference across 5 model variants with Pinecone-backed semantic retrieval. Developed Ray-based distributed utilities adopted by 20+ ML engineers, reducing experiment turnaround by 30%. Replaced legacy rule-based systems with deep learning

Machine Learning Engineer at Cognizant

November 1, 2020 - December 1, 2023

Built and maintained enterprise MLOps infrastructure using Docker, Kubernetes, Terraform, and CI/CD, reducing deployment cycles from 4 weeks to 3 days and enabling autoscaling across 1M+ daily API calls. Developed scalable ETL and data processing pipelines using PySpark, Apache Airflow, AWS EMR, and AWS Glue, processing 5+ TB of customer data daily and improving pipeline runtime by 20% (5h → 4h). Enhanced conversational AI and NLP solutions using BERT, Amazon Lex, and AWS Comprehend, increasing chatbot engagement from 62% to 77% and reducing unhandled customer queries by 28% across 5 retail and healthcare clients. Developed XGBoost churn prediction model (85% AUC) and K-means clustering across 5 clusters, contributing to $2.4M in annual cross-sell revenue uplift. Built time-series forecasting models on 20M+ sensor records, reducing unplanned downtime by 12% and delivering $1.8M in annual savings. Applied Bayesian Optimization, GridSearchCV, and feature engineering across 8 platform m