Pre-screened and vetted.
Junior AI/ML Engineer specializing in LLMs, automation, and backend data pipelines
Entry-level Machine Learning Engineer specializing in LLMs, RAG, and data pipelines
Mid-level Software Engineer specializing in backend systems, data pipelines, and AI/RAG
Mid-level Full-Stack Engineer specializing in backend systems and AI integration
Mid-level Full-Stack AI Engineer specializing in web and generative AI solutions
Mid-level Backend/Full-Stack Software Engineer specializing in AWS, Node.js, and AI integrations
Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP
Mid-Level Full-Stack Engineer specializing in UX-focused web platforms
Mid-level Software Developer specializing in C++ and Unreal Engine AI systems
Mid-level Generative AI Engineer specializing in LLMs, RAG, and agentic systems
Mid-Level Full-Stack Software Engineer specializing in cloud microservices and Voice AI
Mid-level Back-End Engineer specializing in scalable APIs and multi-tenant systems
Junior Full-Stack Software Engineer specializing in logistics and IoT systems
Mid-level DevOps & Customer Success Engineer specializing in cloud, networking, and GenAI
Mid-level Data Engineer specializing in cloud-native batch and streaming pipelines
Junior Full-Stack Developer specializing in Django/React and cloud-native APIs
Senior Full-Stack Engineer specializing in .NET, IoT, analytics, and CRM platforms
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.”
Mid-level Generative AI & ML Engineer specializing in LLMs, RAG, and MLOps