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Vetted MLOps Professionals
Pre-screened and vetted.
Mid-level Data Scientist / GenAI Engineer specializing in LLMs, RAG, and MLOps
Mid-level Data Analyst & ML Engineer specializing in GenAI, NLP, and cloud data pipelines
Mid-level AI Backend Engineer specializing in LLM applications and scalable ML services
Principal Software Engineer specializing in enterprise AI/ML and multi-cloud architecture
Mid-level Software Engineer specializing in backend systems and LLM applications
Mid-level AI Backend Engineer specializing in LLM applications and scalable ML services
Mid-Level Software Developer specializing in FinTech and AI-enabled systems
Mid-level AI/ML Engineer specializing in GenAI, RAG, and cloud-native ML platforms
Mid-level AI/ML Engineer specializing in recommender systems, NLP, and MLOps
Mid-level Full-Stack Developer specializing in FinTech and fraud detection
Mid-level AI/ML Engineer and Developer Educator specializing in GenAI, RAG, and AI community building
Mid-level AI/ML Engineer specializing in MLOps, distributed ML, and RAG pipelines
Senior Data Scientist specializing in Generative AI, NLP, and MLOps
Mid-level Data Engineer specializing in AI/ML data platforms and real-time streaming
Mid-level Data Engineer specializing in cloud lakehouse and streaming pipelines
Abhishikth Meesala
Mid-level AI/ML Engineer specializing in NLP, Generative AI, and fraud detection
“At PwC, built and productionized an agentic RAG enterprise search assistant over 6M internal documents (8M embeddings), deployed across AWS and GCP. Drove major retrieval gains (72%→92% precision via BM25+dense hybrid with RRF and cross-encoder re-ranking), reduced hallucinations 30%, achieved <2s latency at 50–60K queries/month, and cut support tickets 30%—boosting adoption to 2,500 users by adding source-cited answers.”