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Vetted Model Fine-tuning Professionals
Pre-screened and vetted.
Mid-level Data Scientist specializing in MLOps, forecasting, and generative AI
Mid-level Full-Stack Software Engineer specializing in cloud, microservices, and ML-ready platforms
Senior AI/GenAI Product Leader specializing in enterprise LLM platforms and agentic automation
Mid-level Full-Stack Developer specializing in cloud-native web apps and FinTech integrations
Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and agentic RAG systems
Junior AI/Machine Learning Engineer specializing in healthcare applications
Senior Machine Learning Engineer specializing in Generative AI RAG systems
Senior Software Engineer specializing in AI agents and computer vision
Mid-level Generative AI Engineer specializing in LLMs, RAG, and agentic AI
Mid-level Data Scientist / ML Engineer specializing in LLMs and predictive analytics
Bryan Holland
Executive AI Product & Controls Engineering Leader specializing in agentic video editing and EV systems
“Startup builder (MagicSeven) who designed and implemented a browser-based, agentic video editor end-to-end, including an AWS event-driven multimodal LLM “indexing” pipeline and an orchestration LLM agent for searching and manipulating footage. Demonstrates deep video file/codec knowledge plus practical production hardening of LLM workflows (format validation, plan/execute, S3-based state for debuggability).”
Guillermo Salas
Executive software engineering leader specializing in AI-augmented Healthcare SaaS platforms
“VP-level software engineering leader in a private-equity-backed company, overseeing a 50+ person org through aggressive growth and operational efficiency goals. Particularly strong in building the operating system around engineering—product-to-engineering governance, AI-augmented SDLC practices, ADRs, and feature-flag-driven delivery—to reduce ambiguity, dependency on institutional knowledge, and cycle time.”
Abnik Ahilasamy
Intern LLM/GenAI Engineer specializing in RAG, agentic systems, and low-latency inference
“Interned at Larsen & Toubro where they built and deployed an agentic RAG document question-answering system to reduce time spent searching documents and improve trustworthiness. Implemented ReAct-style multi-step orchestration with LangChain/LlamaIndex plus evidence-bounded generation, grounding/citations, and rigorous evaluation—cutting latency ~40%, hallucinations ~35%, and unsafe outputs ~40% while collaborating closely with non-technical business/ops stakeholders.”
Alex Nguyen
Junior Applied AI Engineer specializing in LLMs, RAG, and agentic systems
“Co-founded a healthcare AI startup building and deploying software directly with end users, emphasizing rapid shipping, deep user interviews, and workflow-first adoption. Has hands-on production deployment experience on AWS (including diagnosing a silent AWS App Runner failure caused by an ARM vs amd64 Docker build mismatch) and is motivated by customer-facing, travel-heavy roles to keep engineering tightly connected to real-world usage.”