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Vetted Vector Databases Professionals
Pre-screened and vetted.
Durgaprasad G
Mid-level AI/ML Engineer specializing in LLM infrastructure, RAG, and agentic systems
“Stripe engineer who owned and unified multiple team RAG systems into a shared production platform used by 200+ internal operators, deployed on EKS with Kafka ingestion and hybrid retrieval. Drove measurable business outcomes including <400ms latency, ~35% inference cost reduction, ~25% accuracy lift via fine-tuning, and real-time auto-approval of 80%+ merchant compliance applications through strong observability and reliability patterns.”
Christopher huebner
Senior Unity/Full-Stack Engineer specializing in distributed systems, VR, and AI/LLM integration
“Unity/C# gameplay engineer who has shipped a modular, data-driven combat ability system with strong measurable outcomes (≈80% fewer GC allocations, 15–20% better frame times, 10–12% higher early retention). Also integrated an LLM-driven NPC dialogue/quest hint system with a C#/.NET backend, caching/guardrails, and telemetry-driven iteration, and shipped Photon PUN real-time 4-player co-op plus a shared codebase across Meta Quest VR and iOS/Android.”
“Data science/NLP practitioner with experience at NVIDIA and Microsoft building production-grade NLP and data-linking systems. Has delivered high-performing pipelines (e.g., F1 0.92) and large-scale entity resolution (F1 0.89), plus semantic search using embeddings and Pinecone with ~30–40% relevance gains, backed by rigorous validation (A/B tests, ROUGE, MRR) and strong MLOps/workflow tooling (Airflow, Databricks, FastAPI, MLflow, Prometheus/ELK).”
Manasseh Mannem
Mid-level DevOps Engineer specializing in AWS, Azure, Kubernetes, and cloud automation
“Built and owned end-to-end deployment and AI support workflows spanning CI/CD, Kubernetes, Terraform, and LLM/RAG systems. Stands out for combining DevOps delivery with production AI operations, including secure tool-calling, incident debugging, retrieval quality controls, and validation-first document ingestion for messy real-world inputs.”
Mid-level Software Engineer specializing in robotics, AI, and full-stack systems
Mid-level Backend/Platform Engineer specializing in AWS, Kubernetes, and FinTech automation
Senior Software Engineer specializing in distributed systems, AI/ML platforms, and cloud-native SaaS
Intern Software Engineer specializing in full-stack development and machine learning
Senior AI & Data Engineer specializing in LLM agents, RAG, and data platforms
Director of Engineering specializing in capital markets risk, trading systems, and AI/ML platforms
Mid-level Software Engineer specializing in cloud platforms and distributed backend systems
Senior AI/ML Engineer specializing in LLMs, NLP, and production ML systems
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and real-time recommendation systems
Junior Software Engineer specializing in LLMs, Agentic AI, and MLOps
Senior Full-Stack Engineer specializing in cloud-native microservices and AI/LLM integrations
Intern AI Product Manager specializing in enterprise AI security and agent platforms
Staff Machine Learning Engineer specializing in LLMs, recommendations, and MLOps
Principal AI Architect specializing in GenAI, agentic systems, and RAG
Executive Software Engineering Leader specializing in digital transformation and omnichannel commerce
Senior Data Scientist specializing in GenAI and LLM systems for financial services
Junior AI Prompt Engineer specializing in LLMs, RAG, and conversational AI
Senior AI and Full-Stack Engineer specializing in Healthcare IT and FinTech