Vetted Predictive Modeling Professionals

“AI/back-end engineer at Canon who helped build and operate an internal production LLM platform that acts as a secure middle layer between users and models, defending against jailbreaks/prompt injection while enabling RAG, memory, and grounded responses over company data. Experienced with LangChain/LangGraph orchestration, vector DB retrieval, and reliability practices (testing, monitoring, adversarial prompts) to run high-throughput, low-latency AI workflows in production.”

“IT Analyst/research background with hands-on experience deploying and hardening a multi-agent AI support/triage system (ticket ingestion + knowledge-base retrieval) with strong emphasis on reliability and observability. Has debugged real production issues spanning backend services and network latency (sync failures/partial writes) and is comfortable in Linux environments; also has academic exposure to robotics simulation and ROS2.”

“Backend engineer who rebuilt and refactored high-traffic systems at Phenom using Java/Spring Boot/Play and also designs Python/FastAPI services. Focused on measurable reliability and performance gains through DB/query optimization, async processing, and strong observability, with disciplined rollout practices (feature flags, parallel runs, rollback) and security patterns including token auth and row-level security.”

“Unity/C# developer with hands-on Meta Quest shipping experience from Wren Kitchens, building a VR kitchen scale visualiser and solving tricky URP/HDRP cross-pipeline rendering issues by creating internal shader/asset management utilities. Also has solo Unity game experience including an Android/Google Play release and game jam prototyping, plus side-project work using Python/PyTorch for predictive modeling.”

“Data/ML practitioner who has built a production RAG-based knowledge assistant integrated into Microsoft 365/internal dashboards to help employees query internal documents in plain English. Experienced orchestrating and hardening ETL pipelines with Airflow and Azure Data Factory (validation, retries, monitoring) and running end-to-end model evaluation and production performance tracking via Power BI.”

“Unity gameplay programmer with experience on TT Games' LEGO Star Wars Battles, including adding full controller support to a touch-first unit deployment system and implementing new networked unit mechanics in a Photon-based multiplayer layer. Has worked in client-server architectures (including Metaplay-backed servers), with a focus on refactoring for reusable combat/damage code and scalable analytics instrumentation.”

“Backend/AI engineer who has built production LLM orchestration and agentic workflow systems in Python/FastAPI on Kubernetes across AWS/Azure. Demonstrated strong reliability engineering by debugging a real-world memory retention issue that caused latency spikes/timeouts, and strong data/performance chops with a PostgreSQL optimization that cut query latency from ~1.2s to ~15ms. Targets roles building scalable, guardrailed AI-driven workflow automation with robust observability and human-in-the-loop controls.”