.png){kind=logo}
Vetted Feature Engineering Professionals
Pre-screened and vetted.
Junior Computer Vision Engineer specializing in AI/ML and transformer-based vision models
Mid-level Machine Learning Engineer specializing in Generative AI and LLMOps
Mid-level Data Scientist / GenAI Engineer specializing in LLM agents, RAG, and OCR
Mid-level Data Analyst specializing in policy research and stakeholder-ready data storytelling
Intern Full-Stack/Backend Developer specializing in web APIs and data processing
Junior Software Engineer specializing in AI data pipelines and full-stack development
Junior Full-Stack Software Engineer specializing in cloud-native healthcare applications
Mid-level Full-Stack & AI Engineer specializing in FinTech and ML-powered applications
Mid-level Machine Learning & Robotics Engineer specializing in autonomous UAVs and biomedical ML
Junior Machine Learning Engineer specializing in scalable ML systems and LLMs
Junior AI/ML Engineer specializing in Generative AI production systems
Mid-Level Software Developer specializing in AI/ML and cloud-native microservices
Senior Software Engineer specializing in AI/ML and cloud backend systems
Intern AI/ML Engineer specializing in NLP, graph analytics, and agentic RAG systems
Mid-level AI/ML Engineer specializing in risk modeling, healthcare analytics, and MLOps
Senior Data Engineer specializing in Machine Learning and Healthcare Data Platforms
Mid-level AI Engineer specializing in agentic LLM workflows and RAG systems
Avni Tripathi
Mid-level Data Scientist specializing in NLP, RAG, and information retrieval for RegTech
“Built and deployed a production document Q&A/research platform that combines semantic search (vector DB embeddings) with structured knowledge-graph querying to reduce analyst research time. Used in high-stakes domains like Politically Exposed Person profiling and extracting critical information from ESG/regulatory documents, with a human-in-the-loop evaluation process (precision@k and source-text highlighting) to ensure accuracy.”
Dhairya Shah
Entry-level Machine Learning Engineer specializing in computer vision and systems
“ML-focused builder who has shipped an end-to-end income-class prediction product: built the data pipeline, trained models, deployed via Streamlit with a live UI, and tracked success via accuracy (84%), adoption, and latency. Demonstrates strong practical MLOps instincts (Docker/Streamlit Cloud, logging/monitoring, caching) and data engineering reliability patterns (schema checks, idempotency, retries, backfills) while iterating quickly in ambiguous, solo-project environments.”