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Vetted Machine Learning Professionals
Pre-screened and vetted.
Entry-Level Software Engineer specializing in full-stack JavaScript and machine learning
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices
Mid-level Database Developer specializing in SQL, ETL, and cloud data platforms
Mid-level Generative AI Engineer specializing in LLMs, RAG, and prompt engineering
Senior Full-Stack Engineer specializing in Python/Flask, React, and autonomous AI systems
Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP
Intern Software Engineer specializing in cloud infrastructure, DevOps, and AI-enabled systems
Senior Data Scientist / ML Engineer specializing in NLP, speech AI, and computer vision
Junior Full-Stack Software Engineer specializing in Python/React and AI-powered web apps
Entry-Level Full-Stack Engineer specializing in backend APIs and cloud architectures
Mid-level AI & Data Science professional specializing in MLOps, deep learning, and UAV research
Junior Full-Stack Developer specializing in AI integrations and LLM research
Mid-Level Full-Stack Software Engineer specializing in cloud microservices and Voice AI
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
Mid-Level Full-Stack Software Engineer specializing in web apps and AI-powered tools
Mid-level DevOps & Customer Success Engineer specializing in cloud, networking, and GenAI
Jeevan Kumar
Mid-level Full-Stack AI Engineer specializing in LLM systems and RAG
“Built and shipped a production "Campaign AI" multi-agent system (LangGraph) that personalizes B2B outbound emails at scale using Apollo.io prospect data, clustering-based segmentation, and 21 persona variants. Notably uncovered that high click rates were largely email security scanners and created a validated bot-detection/scoring pipeline (timestamps/IP/user-agent/click patterns), bringing reported engagement down from ~40% to a trusted 5–8% that aligned with real conversions.”
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.”