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Vetted Deep Learning Professionals
Pre-screened and vetted.
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and document intelligence
Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and RAG for financial services
Mid-level Machine Learning Engineer specializing in NLP, recommender systems, and MLOps
Mid-level Software Engineer specializing in cloud-native microservices and ML-driven automation
Senior Machine Learning Engineer specializing in Generative AI and NLP
Mid-level Full-Stack Engineer specializing in Python, FastAPI, and cloud-native systems
Senior AI/ML Engineer specializing in Generative AI and Computer Vision
Mid-level Software Engineer specializing in AI, data engineering, and cloud systems
Mid-level AI/ML Product & Solutions Specialist specializing in GenAI and MLOps
Mid-level Machine Learning Engineer specializing in LLMs, multimodal AI, and backend systems
Principal Data Scientist specializing in AI/ML forecasting and MLOps
Mid-level AI/ML Engineer specializing in forecasting, MLOps, and generative AI
Mid-level Data Engineer specializing in GCP, Spark, and healthcare analytics
Adithya Rajendra
Junior Data Engineer specializing in Azure data platforms and GenAI analytics
“Data/ML practitioner with experience spanning medical imaging (retinal vessel analysis for hypertension/CVD risk prediction) and enterprise data engineering at Carl Zeiss. Built large-scale SAP data cleaning/validation pipelines (10M+ daily records, ~99% accuracy) and RAG-based semantic search with LangChain/vector DBs that cut manual querying by 82%, plus automation that reduced data onboarding from 8 hours to 12 minutes.”