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Vetted Java Professionals
Pre-screened and vetted.
Mid-Level Full-Stack .NET Engineer specializing in cloud, APIs, and data analytics
Junior Software Engineer specializing in backend systems and RAG applications
Senior Software QA Engineer specializing in test automation and CI/CD
Intern Full-Stack Software Engineer specializing in cloud, microservices, and ML/NLP
Senior Technical Artist specializing in Unreal Engine pipelines and real-time cinematics
Mid-Level Software Engineer specializing in AI/ML, cloud deployment, and full-stack systems
Senior Cloud & DevOps Engineer specializing in AWS migration, IaC, and CI/CD
Junior Financial Data Analytics and Programming Candidate
Senior Full-Stack/Backend Engineer specializing in distributed systems and cloud-native platforms
Mid-level Full-Stack Developer specializing in Java, Spring Boot microservices, and Angular
Senior Full-Stack Developer specializing in automation, IoT, and integrations
Senior QA Automation Engineer specializing in BDD and Selenium automation for P&C insurance
Senior QA Engineer specializing in manual and Selenium-based test automation
Senior Java Developer specializing in cloud-native microservices and event-driven systems
Senior Full-Stack Engineer specializing in Python back-end systems and scalable web apps
Senior Unity/C# Developer specializing in performance, rendering, and VR
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.”