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Vetted Hugging Face Professionals
Pre-screened and vetted.
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
Sadir Ahmed Zidan
Junior AI/ML Engineer specializing in LLMs, RAG, and computer vision
“AI engineer with hands-on experience shipping production systems across semantic search, RAG/LLM applications, and computer vision. Built a personalized e-commerce search platform with measurable relevance and latency gains, and deployed grounded GenAI chat systems that significantly reduced hallucinations while lowering support burden. Also brings edge-deployment experience in monocular depth estimation and 3D reconstruction, suggesting strong breadth across modern applied AI.”
Entry-Level Full-Stack AI Engineer specializing in RAG pipelines and enterprise SaaS
Entry-level Software Engineer specializing in AI/ML and full-stack systems
Junior Full-Stack Software Developer specializing in cloud-native apps and data/AI
Junior Machine Learning Engineer specializing in LLMs, RAG, and fine-tuning
Mid-level AI/ML Engineer specializing in LLMs and RAG systems
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Mid-level AI Engineer specializing in LLMs, RAG, and enterprise compliance & fraud systems
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Mid-level AI Software Engineer specializing in LLM agents and RAG systems
Mohammad Al-Hudban
Intern AI Engineer & Data Scientist specializing in GenAI, LLMs, and RAG
“Currently working at CBS Lab in Austria, where they implemented/replicated the "Open World Grasping" research pipeline end-to-end. Built a ROS-based RGB-D perception-to-action system using SAM 2.1 segmentation and MoveIt motion planning to generate grasp poses and execute pick-and-place/sorting with a robotic arm.”
Tanushree Kakad
Intern Software Engineer specializing in AI, computer vision, and VR
“Robotics software engineer with hands-on experience integrating vision-based perception with control logic in ROS simulation environments. Focused on debugging real-time timing/data-flow issues, improving system stability through incremental scenario testing in Gazebo, and supporting reliable deployments with Docker and basic CI/CD automation.”
“Built and shipped a production-grade RAG-powered news summarization and Q&A product, tackling real-world issues like retrieval drift, hallucinations, latency, and autoscaling deployment (Docker + FastAPI + Streamlit Cloud). Experienced in end-to-end ML/LLM workflow automation using Airflow, Kubeflow Pipelines, and MLflow, and has demonstrated business impact (40% inference precision improvement) through close collaboration with non-technical stakeholders at Evoastra Ventures.”