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Vetted Machine Learning Engineers
Pre-screened and vetted.
Junior Machine Learning Engineer specializing in LLM infrastructure and inference optimization
Mid-level AI/ML Engineer specializing in LLM, RAG, and agentic systems
Mid-level Machine Learning Engineer specializing in Generative AI, LLMs, and MLOps
Mid-level AI/ML Engineer specializing in LLMs, NLP, and MLOps
Mid-level GenAI/MLOps Engineer specializing in banking and healthcare LLM applications
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and cloud deployment
Mid-level Machine Learning Engineer specializing in MLOps, fraud detection, and data security
Mid-level Machine Learning & AI Engineer specializing in LLMOps, digital twins, and RL
Mid-Level Full-Stack Engineer specializing in AI/ML and cloud-native web apps
Mid-level Machine Learning Engineer specializing in MLOps and Generative AI
Senior Machine Learning Software Engineer specializing in Azure enterprise AI
Mid-Level Software Engineer specializing in ML and healthcare data systems
Mid-level AI/ML Engineer specializing in LLM fine-tuning and RAG for healthcare
Mid-level Data Science & AI/ML Engineer specializing in MLOps, NLP, and computer vision
Junior Machine Learning Software Engineer specializing in cloud-deployed predictive models
Junior Machine Learning Engineer specializing in healthcare AI and GenAI RAG
Mid-level Machine Learning Engineer specializing in production ML, MLOps, and Generative AI
sai anuragh Sangoju
Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP
“Built and deployed a production LLM-powered university support chatbot on Azure using a RAG pipeline, focusing on reducing hallucinations, improving latency, and handling ambiguous queries via confidence checks and clarification prompts. Also has hands-on orchestration experience (Airflow/Azure Data Factory), including hardening a demand-forecasting ingestion workflow with sensors, retries, and automated alerts, and uses a metrics-driven testing/monitoring approach for reliable AI agents.”
Vamsidhar Vuddagiri
Mid-level AI/ML Engineer specializing in LLMs, MLOps, and Azure
“AI/ML engineer who led Impacter AI’s production deployment of a specialized outreach LLM (CharmedLLM) fine-tuned on GPT-4.1, cutting API costs ~40% while boosting outreach effectiveness ~60%. Built the supporting MLOps and data infrastructure (MLflow, Kubernetes, PySpark, Kafka) and has agentic AI experience from University of Dayton, using LangChain + RAG and vector search (Pinecone) to improve reliability and reduce hallucinations.”
Mid-level AI Engineer specializing in LLM, RAG, and multi-agent systems