Pre-screened and vetted.
Mid-Level Software Engineer specializing in distributed microservices and cloud-native systems
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
Junior AI Engineer specializing in production RAG systems and GPU-accelerated inference
Entry-level Full-Stack Engineer specializing in AI-powered applications
Mid-level Full-Stack AI Engineer specializing in agentic AI and RAG systems
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).”
“Full-stack AI engineer who has built and deployed multiple end-to-end LLM products, including an AI interview assistant, a multi-agent market research platform, and a policy document explainer. Particularly strong in productionizing agentic workflows, integrating tools like Whisper, Tavus, LiveKit, CrewAI, and LangGraph, and hardening messy real-world AI/document pipelines with validation, memory isolation, and fallback handling.”
Junior Full-Stack Engineer specializing in AI-powered web applications
“Full-stack product engineer who has shipped AI-powered job board moderation and validation features end to end across React/TypeScript, serverless backends, and Postgres. Stands out for combining UX polish, LLM-backed workflow design, and reusable async infrastructure patterns to improve reliability, speed of delivery, and user participation.”
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.”
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.”
Mid-level Generative AI & ML Engineer specializing in LLMs, RAG, and MLOps
Mid-Level .NET Software Engineer specializing in backend APIs, Azure, and SQL Server
Junior Software/AI Engineer specializing in LLM agents and RAG systems
Entry-Level Full-Stack & AI Engineer specializing in chatbots and web apps
“Data Science honors graduate (Maryville University) who has built Python/SQL backends and a capstone website handling sensitive user data. Emphasizes secure data handling (password encryption, secure database updates) and uses Git/GitHub Pages with CI/CD-style practices for managing and deploying changes.”
Executive Founder-CTO specializing in AI agents and distributed systems
Mid-level Game Developer specializing in Unity, AR/VR, and cross-platform products
“Exceptionally young game developer who says he began at age 10 and was employed as a Unity developer at 13. He has hands-on experience building gameplay systems, VR/Web/mobile projects, Photon multiplayer features, and AI/ML experiments—including an open-source protein-model research pipeline reportedly under peer review at PLOS ONE.”
Mid-level Machine Learning Engineer specializing in NLP, Computer Vision & Predictive Analytics
“Built a production LLM fine-tuning pipeline for domain-specific code generation at Pigeonbyte Technologies, including automated collection and rigorous quality filtering of 10M+ code samples (AST validation, sandbox execution/testing, deduplication, drift monitoring, and human-in-the-loop review). Also implemented end-to-end ML orchestration in Apache Airflow with data quality gates, dataset versioning in S3, benchmarking, and automated model promotion, and has a reliability-first approach to agent/workflow design.”
Mid-level Unity Developer specializing in R&D and AI-driven gameplay systems
“Unity/C# gameplay engineer based in Portugal who shipped an AI-driven NPC narrative/quest system for a live mobile RPG, integrating Google Gemini via function-calling with strict JSON schemas to keep a deterministic game loop safe from hallucinations. Emphasizes high-performance engineering (zero per-frame GC, locked 60 FPS) with rigorous PR reviews and profiling gates, plus robust async/network patterns (UniTask, CancellationTokens) and LLM cost control via sliding-window context management. Seeking independent B2B contractor work at $45k–$50k USD/year.”
Entry-level Software Engineer specializing in backend and full-stack systems
“Built production-style backend and AI systems across internship and project work, including a real-time sports platform backend and a Smart Email Assistant using GPT-4. Stands out for combining classic backend performance engineering with practical LLM workflow design, including measurable latency improvements, high uptime, and debugging of non-deterministic model behavior.”
Senior Unity Developer specializing in desktop and XR simulation apps
“Unity/C# developer who built and continues to evolve a data-driven product configuration system for complex medical equipment—reverse-engineering undocumented, massive databases and generating 3D configured products with extensive rules—helping users (e.g., hospital sales workflows) save time and support increased sales. Also built an internal LLM-powered debugging assistant using structured Unity/backend telemetry and has hands-on Unity Netcode experience in smaller multiplayer prototypes.”