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Vetted Computer Vision Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in scalable ML systems and cloud MLOps
Senior Solutions Engineer specializing in Enterprise SaaS and AI solutions
Mid-level Machine Learning Engineer specializing in NLP, LLMs, and deep learning
Junior Full-Stack Software Engineer specializing in ML, cloud infrastructure, and LLM agents
Mid-level Machine Learning Engineer specializing in NLP, LLMs, and MLOps
Mid-level Data Scientist / GenAI Engineer specializing in LLMs, RAG, and MLOps
Principal Software Engineer specializing in enterprise AI/ML and multi-cloud architecture
Mid-level AI Engineer specializing in LLM agents and multimodal generative AI
Mid-level Backend Software Engineer specializing in microservices and cloud APIs
Mid-Level Software Engineer specializing in distributed systems and FinTech
Mid-level AI/ML Engineer specializing in recommender systems, NLP, and MLOps
Mid-level AI Engineer specializing in LLM agents, RAG, and enterprise GenAI
Junior Multimodal AI & Systems Engineer specializing in robotics and cloud infrastructure
Mid-level AI/ML Engineer and Developer Educator specializing in GenAI, RAG, and AI community building
Executive Product & Technology Leader specializing in AI and healthcare platforms
Deepam Ameria
Intern Robotics Software Engineer specializing in autonomy, perception, and control
“Robotics software engineer with hands-on experience building autonomy features across perception, planning, and systems integration—most notably for an autonomous lunar rover that detects and geometrically models craters to plan terrain manipulation. Also owned development of an autonomous stair-climbing module for a quadruped robot as an intern, and has real-time motion-planning/IK debugging experience on a Franka Panda using RGB-D (RealSense).”
Harinee Mohanakrishnan
Junior AI/ML & Cloud Software Engineer specializing in LLM applications
“AI engineer (2+ years; pursuing an online MS at UIUC) who has shipped an AI-powered voice screening platform end-to-end on GCP with strong production monitoring and measurable hiring-process impact (80% reduction in unqualified pass-through; ~50+ hours saved per role). Also built and deployed an AWS-based context-aware hybrid search system using OpenSearch as a vector store, and has hands-on experience with multi-agent LLM orchestration (ReAct) and structured-output guardrails.”