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Vetted Model Fine-tuning Professionals
Pre-screened and vetted.
Junior AI/ML Engineer specializing in LLMs, RAG systems, and MLOps
Senior AI/ML Engineer specializing in Generative AI, RAG, and multimodal LLM systems
Mid-level Robotics & Edge AI Engineer specializing in teleoperation, SLAM, and computer vision
Director-level Applied ML Engineer specializing in GenAI, LLM systems, and MLOps
Senior Software Engineer specializing in AI/ML and cloud backend systems
Mid-Level ML/AI Engineer specializing in LLMs, RAG, and multi-agent systems
Mid-level Generative AI Engineer specializing in LLMs, RAG, and NLP systems
Junior Full-Stack Software Engineer specializing in cloud, distributed systems, and AI
Prasad Sadineni
Mid-level AI Engineer specializing in LLM fine-tuning, RAG, and agentic systems
“Building and deploying production in-house, domain-specific LLM chatbots for enterprises that cannot use third-party GPT tools due to internal policies. Focused on reducing latency and improving domain awareness using fine-tuning, continual learning, and advanced RAG/agent retrieval strategies, with experience orchestrating multi-agent workflows via LangChain/LlamaIndex and vector DBs (FAISS, Weaviate, Chroma).”
Shehab mohamed mohamed
Junior AI Engineer specializing in MLOps, LLMs, and multi-agent systems
“ML/AI engineer focused on production-grade systems, with experience building a low-latency multi-agent 'neural concierge' booking platform used across domains like restaurants and hospitals. Also worked on a healthcare computer vision system for nystagmus/eye-movement analysis, showing a mix of scalable LLM infrastructure, MLOps, and safety-conscious medical AI experience.”
Karthikeya Arra
Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and MLOps
“Backend/ML engineering candidate focused on fintech automation who architected a zero-to-one agentic/LLM-enabled system to reconcile messy financial documents and bank transactions, reporting ~40% operational efficiency gains. Experienced migrating monoliths to event-driven microservices with incremental rollout via reverse proxy, and implementing production-grade security (OAuth2/JWT, RBAC, Supabase RLS) plus resilience patterns (timeouts/retries under concurrency).”
Mid-level Full-Stack/AI Engineer specializing in LLM microservices, RAG, and data pipelines
Junior Machine Learning Engineer specializing in LLMs and multimodal AI
Junior Full-Stack Engineer specializing in cloud and AI-integrated web applications
Senior Full-Stack Engineer specializing in AI, SaaS, and IoT platforms
Mid-level AI/ML Research Engineer specializing in NLP, LLM agents, and multimodal systems