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Vetted Recurrent Neural Networks (RNN) Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in generative AI, NLP, and MLOps
Mid-level Data Scientist specializing in deep learning, NLP, and time-series forecasting
Mid-level AI/ML Engineer specializing in LLMs, RAG, and scalable model deployment
Mid-level AI/ML Engineer specializing in risk modeling, healthcare analytics, and MLOps
Mid-level AI Engineer specializing in agentic LLM workflows and RAG systems
Bhargav Kommineni
Intern Full-Stack/ML Engineer specializing in cloud-native web apps and LLM systems
“Machine learning lab assistant at Eastern Illinois University who productionized a voice-enabled conversational AI system: redesigned it with RAG, LoRA fine-tuning (including text-to-SQL), and safety guardrails, then deployed a scalable API supporting ~1,000 daily queries. Also partnered with customer-facing teams during a BlueFi internship by building demos/APIs and accelerating releases via Terraform + AWS CI/CD automation.”
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 AI/ML Engineer specializing in LLMs, RAG, and applied NLP
Entry-Level Data Scientist specializing in machine learning, NLP, and cloud analytics
Intern Full-Stack & AI Engineer specializing in ML-driven mobile and data platforms
Mid-level Generative AI Engineer specializing in LLMs, RAG, and MLOps
Mid-level Java Full-Stack Developer specializing in cloud microservices and AI/ML integration
Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP
Entry-Level Full-Stack Engineer specializing in backend APIs and cloud architectures
Jeevan Kumar
Mid-level Full-Stack AI Engineer specializing in LLM systems and RAG
“Built and shipped a production "Campaign AI" multi-agent system (LangGraph) that personalizes B2B outbound emails at scale using Apollo.io prospect data, clustering-based segmentation, and 21 persona variants. Notably uncovered that high click rates were largely email security scanners and created a validated bot-detection/scoring pipeline (timestamps/IP/user-agent/click patterns), bringing reported engagement down from ~40% to a trusted 5–8% that aligned with real conversions.”
Mid-level Generative AI & ML Engineer specializing in LLMs, RAG, and MLOps
Aditya Reddy Gunda
Intern AI/ML & Data Engineer specializing in deep learning, NLP, and cloud data pipelines
“AI/ML practitioner with production experience building a RAG-powered contextual customer support agent, optimizing for low latency using vector databases and smaller LLMs. Also deployed a fraud detection model on Kubernetes with auto-scaling for heavy transactional loads, and improved chatbot accuracy by 15% through metric-driven testing and evaluation. Partners with Marketing on personalization/recommendation initiatives with measurable outcomes tied to customer feedback.”