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Vetted Hugging Face Professionals
Pre-screened and vetted.
Mid-Level AI/Full-Stack Engineer specializing in conversational AI and SaaS products
Intern Data Scientist specializing in LLM agents, RAG, and real-time ML pipelines
Mid-Level Full-Stack Software Engineer specializing in cloud-native systems
Mid-level Software Engineer specializing in IoT, robotics, and secure edge-to-cloud systems
Mid-level Machine Learning Engineer specializing in MLOps, NLP, and Computer Vision
Mid-level AI/ML Research Engineer specializing in NLP, LLM agents, and multimodal systems
Mid-level Software Engineer specializing in Generative AI and cloud-native microservices
Mid-level Generative AI Engineer specializing in LLMs, RAG, and MLOps
Junior Generative AI Engineer specializing in LLM systems and RAG
Mid-level Java Full-Stack Developer specializing in cloud microservices and AI/ML integration
Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP
Mid-level Generative AI Engineer specializing in LLMs, RAG, and agentic systems
Junior Full-Stack Developer specializing in AI integrations and LLM research
Mid-level AI/ML Research Engineer specializing in NLP, LLM agents, and multimodal systems
Mid-level AI/ML Engineer specializing in GenAI, agentic AI, and RAG pipelines
Haeshitha Indukuri
Entry AI/ML Engineer specializing in Generative AI, LLMs, and MLOps
“Built and productionized a MediCloud/Medicoud LLM microservice platform that lets clinicians query medical data in natural language, orchestrating multi-step RAG-style workflows with LangChain and evaluating/debugging with LangSmith. Delivered measurable gains (consistency ~70%→90% / +20%; latency ~2.0s→1.1s / -40%) by implementing structured prompts, fallback logic across multiple LLMs, hybrid retrieval tuning, and AWS Lambda performance optimizations (package size, async, caching).”
Harshit Vashisth
Junior AI Engineer specializing in LLMs, RAG systems, and MLOps
“Robotics software engineer who built an end-to-end system ("justmatrix"), focusing on multi-agent orchestration and a multi-RAG retrieval backend/API. Has hands-on ROS experience, including a custom node for reliable high-frequency sensor data routing, plus deployment automation using Docker, Kubernetes, and CI/CD.”
Junior Software/AI Engineer specializing in LLM agents and RAG systems
Entry-Level Full-Stack AI Engineer specializing in RAG pipelines and enterprise SaaS
Junior Full-Stack/ML Engineer specializing in web automation and NLP