Vetted Deep Learning Professionals

“NVIDIA engineer who built and shipped a production LLM-powered enterprise knowledge system (summarization, transcription, and Q&A) that cut document retrieval time ~30%. Deep hands-on experience with RAG (FAISS/Pinecone), GPU-accelerated microservices on AWS, and reliability/safety practices (Guardrails AI, prompt A/B testing, canary releases) plus strong MLOps orchestration across Airflow, Step Functions, and Kubernetes GitOps.”

“Founder building an enterprise agentic AI startup who has already raised about $100K (friends & family plus self-funding). Has prior and current experience engaging VCs (including outreach to both large and small firms) and emphasizes demo-driven pitching, enterprise customer validation, and targeting billion-dollar market opportunities.”

Martin Bom

Screened

Director-level Engineering Leader specializing in cloud services and large-scale delivery

Amsterdam, Netherlands31y exp

“Engineering leader with a hands-on developer background who has launched and scaled cloud services at AWS (CloudShell) while also leading AWS Cloud9. Built multi-year roadmaps and cross-org stakeholder alignment (product/marketing/mobile), and has a track record of scaling teams (3x growth) by implementing operational excellence, automated quality gates, and security champion programs; advocates serverless architectures to minimize maintenance and accelerate global expansion.”

“Backend/full-stack engineer with experience building large-scale systems on Salesforce and eBay, including a sharded Oracle-backed personalization store used by millions of sellers and a Spring Boot microservice that executes scheduled payouts at high volume. Emphasizes production readiness via state-machine-based idempotency, strong observability (Splunk/Elasticsearch/PagerDuty), and extensive Selenium/Sauce Labs automation.”

“Senior product engineering and data architecture leader who has owned end-to-end solutions for enterprise analytics and legal search platforms, including work for Sony Pictures Entertainment and Accenture Legal. Combines executive-level architecture and team leadership with hands-on experimentation in modern AI systems, recently building a multimodal Hugging Face agent that significantly exceeded its benchmark score.”

“McKinsey practitioner who built and deployed production LLM systems for consultants/clients, including a Power BI-integrated multi-agent chatbot (RAG + text-to-SQL + formatting) with custom Python orchestration, verification loops, and a 100+ case eval set achieving ~95% consistency. Also delivered a taxonomy-mapper agent that standardized inconsistent labeling for C-suite stakeholders, cutting a process from >2 weeks to <30 minutes through demos and business-focused communication.”

“LLM/multimodal systems builder who developed DuetGen, a practical multimodal interleaved text-image generation system using a decoupled MLLM planner and video-pretrained diffusion transformer for high-quality image generation with step-wise alignment. Built a 298K-sample interleaved dataset across 8 domains/151 subtasks and deployed a GPT-5-based automated evaluation framework; also has LangChain-based multimodal agent orchestration experience with custom state management and reliability testing.”