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Vetted GPT-4 Professionals
Pre-screened and vetted.
Senior Data Scientist specializing in ML pipelines and LLM applications
Senior Full-Stack Java Engineer specializing in cloud-native microservices and GenAI
Intern Full-Stack Software Engineer specializing in LLM/RAG and cloud-deployed data apps
Mid-level AI/ML Engineer specializing in GenAI and LLM agent workflows
Senior AI Engineer specializing in Generative AI and cloud-native ML platforms
Mid-level AI/ML Engineer specializing in Generative AI, multi-agent RAG, and FastAPI backends
Junior Full-Stack Engineer specializing in AI/LLM applications
Mid-level Generative AI/ML Engineer specializing in LLMs, RAG, and MLOps
Senior Full-Stack Engineer specializing in cloud-native web platforms and LLM-powered features
Mid-level AI/ML Engineer specializing in LLMs, RAG, and scalable model deployment
Senior Generative AI Engineer & Full-Stack Developer specializing in LLMs and microservices
Mid-level AI Engineer specializing in LLM safety, red teaming, and evaluation
Senior Software Engineer specializing in AI/ML and cloud backend systems
Senior Full-Stack & AI Engineer specializing in FinTech and Healthcare
Senior Sales Development & Account Executive specializing in SaaS, adtech, and social selling
Shreyas Krishnareddy
Junior AI/Software Engineer specializing in NLP, RAG, and resume parsing
“Backend/AI engineer who built and refactored a production RAG system over IRS Form 990 filings for 60 nonprofits, using a dual-path architecture (deterministic financial ranking + TF-IDF semantic retrieval) to keep latency sub-2s and reduce hallucinations. Demonstrates strong API craftsmanship in FastAPI (contract-first, OpenAPI-driven) plus production-grade security for multi-tenant systems (JWT, RBAC, Supabase-style RLS) and careful migration practices (feature flags, traffic mirroring, incremental rollout).”
HarshelSrivatsava Srivatsava
Intern Full-Stack Engineer specializing in AI-powered SaaS products
“Solo builder of OGym, shipping production AI features for gyms that turn member behavior/health data (workouts, attendance, nutrition, payments, device metrics) into prioritized, actionable owner and member insights. Designed and implemented FastAPI backends, PostgreSQL-based RAG workflows, guardrails (RBAC/validation/rate limiting), and real-user evaluation loops, with a strong focus on latency/cost optimization and reliable data pipelines.”
Mid-level ML & Full-Stack Engineer specializing in LLM systems and RAG
Junior Frontend Software Engineer specializing in React, Next.js, and TypeScript