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Vetted Random Forest Professionals
Pre-screened and vetted.
Entry-level Data Analyst specializing in cloud analytics and machine learning
Senior Machine Learning Engineer specializing in NLP and production ML systems
Entry-Level UX Designer and Computer Science Graduate specializing in data-driven product design
Mid-level Full-Stack AI Engineer specializing in RAG systems and intelligent automation
Mid-level AI Engineer specializing in LLMs, RAG, and enterprise compliance & fraud systems
Mid-level Full-Stack Developer specializing in Python, React, and cloud-native microservices
Junior Full-Stack Developer specializing in web apps, cloud, and cybersecurity
Tejaswini E
Entry-level Software Engineer specializing in computer science and applied ML/IoT
“Built a community cleanliness reporting Android app focused on helping citizens and volunteers report illegal waste dumping through maps, image uploads, and real-time updates. Stands out for combining modern Android UI architecture, Firebase-backed real-time features, and practical performance tuning for lower-end devices while keeping the experience simple for general public users.”
Junior Full-Stack Developer specializing in React, Node.js, and AI/ML
Entry AI Engineer specializing in machine learning, computer vision, and data mining
richi ibnu wardana
“Built an automated ML/NLP document classification system for unstructured legal documents, combining classical models (TF-IDF + logistic regression/random forest) with entity resolution via fuzzy matching validated by precision/recall. Also implemented semantic similarity search using sentence embeddings stored in FAISS and improved matching by fine-tuning a transformer on domain-specific data and tuning similarity thresholds for fewer false positives.”
Intern Machine Learning Engineer specializing in NLP, RAG, and time-series forecasting