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Vetted Machine Learning Engineers
Pre-screened and vetted.
Rohanth Gundu
Senior AI/ML Engineer specializing in LLMs, RAG, and MLOps
Aakiff Panjwani
Mid-level AI/ML Engineer specializing in NLP/LLMs and production ML systems
Venkat Kaushik Arutla
Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps
Zikai Liu
Junior AI/ML Engineer specializing in LLM agents, RAG, and multimodal data pipelines
Sushanth Reddy
Senior Machine Learning & GenAI Engineer specializing in LLM systems and data pipelines
Prathamesh Korale
Mid-level Machine Learning Engineer specializing in LLMs, ranking, and scalable ML systems
Keerthana Sherikar
Senior AI/ML Engineer specializing in LLMs, RAG, and multimodal recommendation systems
Saketh Reddy Mandala
Mid-level Machine Learning Engineer specializing in LLM personalization and scalable MLOps
Kiriti Golla
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and MLOps
Richard Chiou
Senior AI/ML Engineer specializing in computer vision, NLP, and real-time forecasting
Srinadh Y
Mid-level AI/ML Engineer specializing in LLMs, multimodal systems, and MLOps
Nihash Chinthala
Mid-level Machine Learning Engineer specializing in real-time recommender systems and MLOps
Syam Sundar Akina
Mid-level AI/ML Engineer specializing in LLMs, RAG, and multi-agent systems
Ram Naresh Goud Balagani
Mid-level AI/ML Engineer specializing in NLP, computer vision, and recommender systems
Harish Kasu
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and MLOps
“AI/LLM engineer with production experience at NVIDIA and Microsoft, including building a RAG-based enterprise knowledge assistant that improved accuracy by 42% and scaled to thousands of queries. Deep in inference optimization (TensorRT-LLM, Triton, quantization, speculative decoding) and MLOps/observability (Prometheus/Grafana, MLflow, LangSmith), plus orchestration with Kubeflow/Airflow across multi-cloud.”
Yishi Wang
Junior Machine Learning & Data Science professional specializing in LLMs and analytics
“Amazon internship experience building production GenAI analytics for the returns organization: a multi-agent LLM+RAG system that let analysts query multiple heterogeneous data sources in natural language without hand-written SQL. Also built and operationalized four Apache Airflow DAGs for large-scale ETL, emphasizing observability and freshness-aware metadata to keep outputs accurate and up to date.”
Chetan Panthukala
Mid-level AI/ML Engineer specializing in LLMs, RAG, and distributed MLOps
Varun narra
Junior ML Engineer specializing in MLOps and real-time inference
Sony Arravena
Mid-level AI/ML Engineer specializing in LLMs, RAG, and production NLP
Satish Mattam
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and scalable GPU inference
Bharath Mamidi
Mid-level AI/ML Engineer specializing in LLMs, RAG, and production MLOps