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Vetted Semantic Search Professionals
Pre-screened and vetted.
Junior Data Systems Analyst specializing in ML, NLP, and cloud deployment
Junior ML Engineer specializing in search, retrieval, and recommendation systems
Entry-level Machine Learning Engineer specializing in LLMs, RAG, and data pipelines
Mid-level Full-Stack Developer specializing in React, Node.js, and AI automation
Junior Generative AI Engineer specializing in LLM systems and RAG
Entry-Level Software Engineer specializing in healthcare data and AI-enabled tools
Mid-level Backend/Full-Stack Software Engineer specializing in AWS, Node.js, and AI integrations
Senior Data Scientist / ML Engineer specializing in NLP, speech AI, and computer vision
Junior AI Engineer specializing in production RAG systems and GPU-accelerated inference
“Early-career full-stack engineer who has not yet shipped a professional customer-facing product but has built sophisticated AI-driven systems in personal/academic work, including a multi-tenant AI knowledge base (async ingestion, pgvector semantic search, SSE real-time updates, knowledge graphs) and an AI-powered code review assistant designed to process thousands of jobs via Redis/BullMQ.”
Entry-Level Full-Stack AI Engineer specializing in RAG pipelines and enterprise SaaS
Junior Full-Stack Software Developer specializing in cloud-native apps and data/AI
Junior Machine Learning Engineer specializing in LLMs, RAG, and fine-tuning
Ramis Hasanli
Intern Cybersecurity Engineer specializing in AI agents and production workflows
“Built and deployed an AI customer representative for iCore used at the IEE convention (2025), serving 100+ users in a day; implemented RAG with a vector database and scaled reliability via Docker and Google Cloud. Also has hands-on experience with multiple agent orchestration stacks (LangChain/LangGraph, Google AI Agent Development Kit, OpenAI SDK, Composio) and has delivered stakeholder-driven apps using prototyping and MVP scoping.”
Manas Kumar Sherla
Junior Machine Learning Engineer specializing in NLP and LLM-based clinical AI
“Built a production automated resume matching system using Python, FAISS vector search, and Selenium-based job scraping, including mitigation for IP blocking and heterogeneous site structures. Also develops LLM/RAG applications with LangChain, using Pydantic-guardrailed structured outputs and LLM-as-a-judge evaluation (including a project focused on tone/semantics for a 3D avatar’s emotional responses).”
Entry-Level Full-Stack Software Engineer specializing in backend systems and cloud deployment