Vetted Generative AI Professionals

“Gameplay-focused Unity developer who prioritizes tight, fair-feeling controls—implemented a custom raycast-based character movement system (avoiding Unity physics) to make platforming more deterministic and difficulty tuning more reliable. Has prototyped multiplayer in both Unity (Photon tic-tac-toe replication prototype) and Unreal Engine (shared workshop/crafting environment), and actively uses AI tools (Copilot + asset generation) to speed prototyping and documentation.”

“AI/ML engineer who led Impacter AI’s production deployment of a specialized outreach LLM (CharmedLLM) fine-tuned on GPT-4.1, cutting API costs ~40% while boosting outreach effectiveness ~60%. Built the supporting MLOps and data infrastructure (MLflow, Kubernetes, PySpark, Kafka) and has agentic AI experience from University of Dayton, using LangChain + RAG and vector search (Pinecone) to improve reliability and reduce hallucinations.”

“UX/Product Designer with experience redesigning a complex enterprise Video Management System (VMS), focusing on the configuration experience—improving flows with dashboards while modernizing UI without breaking legacy users’ mental models. Uses field observation, UX audits, and extensive user testing, and collaborates closely with engineers (HTML/CSS/JS familiarity) to ensure feasibility—e.g., pivoting notification designs from push to widgets based on technical constraints.”

“Built and deployed a production NLP sentiment analysis system at Piper Sandler to turn noisy, finance-specific customer feedback into scalable insights. Demonstrates strong end-to-end MLOps: fine-tuning BERT, improving label quality, monitoring for language drift, and automating retraining/deployment with Airflow and Docker (plus Kubeflow exposure).”

“ML/NLP engineer with Industrial IoT experience who built an end-to-end anomaly detection and GenAI explanation system: AWS (S3, PySpark, EC2/Lambda) pipelines feeding dashboards, plus transformer-embedding vector search to connect anomalies to noisy maintenance notes and past events. Demonstrated measurable impact (15% lift in defect detection; ~35% reduction in manual review; 35% fewer preprocessing errors) and strong productionization practices (orchestration, monitoring, rollback, data-quality controls).”

“ML/NLP engineer focused on large-scale data linking for e-commerce-style catalogs and customer records, combining transformer embeddings (BERT/Sentence-BERT), NER, and FAISS-based vector search. Has delivered measurable lifts (e.g., +30% matching accuracy, Precision@10 62%→84%) and built production-grade, scalable pipelines in Airflow/PySpark with strong data quality and schema-drift handling.”

“Hands-on infrastructure and engineering leader (Director of Global Infrastructure / CTO) who has run double-digit multi-million dollar data center expansion and cloud migration programs and scaled teams rapidly (including offshore/nearshore). Strong AWS and microservices background (Lambda/SQS/SES), with experience balancing deep technical architecture work alongside investor/VC communications and fundraising-related responsibilities.”

“CTO/co-founder who spent the last 6 years running a Singapore venture studio (Undercurrent Capital), performing technical and business due diligence and leading ventures from ideation through growth. Notably built a MAS-regulated bond issuance platform (Cache) for a commodities brokerage, integrating onboarding, back-office, margin calls, and regulated money flows, attracting $120M USD in the first month.”