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Vetted ETL Professionals
Pre-screened and vetted.
Mid-Level Software Engineer specializing in backend, data engineering, and Healthcare IT
Senior Software Engineer specializing in backend, AWS cloud infrastructure, and data pipelines
Mid-Level Software Engineer specializing in backend, cloud, and data pipelines
Mid-Level Software Developer specializing in AI/ML and cloud-native microservices
Junior Software Developer specializing in full-stack and data engineering
Mid-level Full-Stack Software Engineer specializing in real-time web apps and cloud backends
Mid-Level Full-Stack Software Engineer specializing in web apps and data pipelines
Mid-level Full-Stack Java Developer specializing in FinTech and Healthcare
Junior AI/ML Engineer specializing in LLM applications, RAG, and multimodal computer vision
Mid-Level ML/AI Engineer specializing in LLMs, RAG, and multi-agent systems
Senior Full-Stack & AI Engineer specializing in FinTech and Healthcare
Mid-level AI/ML Engineer specializing in risk modeling, healthcare analytics, and MLOps
Senior Data Engineer specializing in Machine Learning and Healthcare Data Platforms
Senior Full-Stack Developer specializing in MERN, cloud platforms, and LLM-powered applications
Senior Full-Stack Python Engineer specializing in AI/LLM-powered web applications
Senior Full-Stack Software Engineer specializing in AI/LLM-powered web applications
Mid-level AI Engineer specializing in agentic LLM workflows and RAG systems
Rukmini Pisipati
Junior AI/ML Engineer specializing in LLM automation and NLP
“Built and shipped a production LLM hallucination detection and monitoring pipeline using semantic-level entropy (embedding-clustered multi-generation variance) to flag unreliable outputs in downstream automation. Implemented a scalable async architecture (FastAPI + Docker + Redis/Celery) with strong observability (structured logs + PostgreSQL) and developed evaluation loops combining controlled prompts and human review; also partnered with non-technical stakeholders on AI-driven form validation/document processing.”
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.”
CharanTeja Kurakula
Entry-Level AI Engineer specializing in NLP and LLM-powered applications
“AI engineer who built an agentic, production-deployed LLM workflow for tobacco violation parsing and automated multi-case creation, using six specialized agents and a human-in-the-loop confidence-threshold routing design. Addressed data privacy constraints by generating synthetic datasets with LLM prompting, and orchestrated reproducible end-to-end pipelines in LangChain with robust testing and evaluation (precision/recall, micro-F1).”