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Vetted MLOps Professionals
Pre-screened and vetted.
Entry-level Machine Learning Engineer specializing in LLMs, RAG, and data pipelines
Mid-level Generative AI Engineer specializing in LLMs, RAG, and MLOps
Junior Generative AI Engineer specializing in LLM systems and RAG
Mid-level AI Engineer specializing in LLM agents, RAG, and evaluation
Mid-level Generative AI Engineer specializing in LLMs, RAG, and prompt engineering
Mid-level Java Full-Stack Developer specializing in cloud microservices and AI/ML integration
Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP
Mid-level AI & Data Science professional specializing in MLOps, deep learning, and UAV research
Mid-level AI/ML Engineer specializing in GenAI, agentic AI, and RAG pipelines
Haeshitha Indukuri
Entry AI/ML Engineer specializing in Generative AI, LLMs, and MLOps
“Built and productionized a MediCloud/Medicoud LLM microservice platform that lets clinicians query medical data in natural language, orchestrating multi-step RAG-style workflows with LangChain and evaluating/debugging with LangSmith. Delivered measurable gains (consistency ~70%→90% / +20%; latency ~2.0s→1.1s / -40%) by implementing structured prompts, fallback logic across multiple LLMs, hybrid retrieval tuning, and AWS Lambda performance optimizations (package size, async, caching).”
Harshit Vashisth
Junior AI Engineer specializing in LLMs, RAG systems, and MLOps
“Robotics software engineer who built an end-to-end system ("justmatrix"), focusing on multi-agent orchestration and a multi-RAG retrieval backend/API. Has hands-on ROS experience, including a custom node for reliable high-frequency sensor data routing, plus deployment automation using Docker, Kubernetes, and CI/CD.”
Mid-level Generative AI & ML Engineer specializing in LLMs, RAG, and MLOps
KARISHMA PAPPU
Junior AI/ML Engineer specializing in machine learning and data pipelines
“Built and productionized an LLM-based system that summarizes large volumes of unstructured content (customer feedback/internal docs) to reduce manual analysis and surface decision-ready insights. Brings strong reliability practices—prompt/schema constraints, validation checks, orchestration with Airflow/Databricks, and rigorous component + end-to-end testing—plus experience partnering closely with business stakeholders to drive adoption.”
Entry-Level Full-Stack AI Engineer specializing in RAG pipelines and enterprise SaaS
Junior Backend/Full-Stack Software Engineer specializing in scalable APIs and cloud platforms
Junior Backend & ML Engineer specializing in Golang microservices and LLM/RAG systems
Mid-level Full-Stack AI Engineer specializing in RAG systems and intelligent automation
Mid-level AI/ML Engineer specializing in LLMs and RAG systems
Mid-level Machine Learning Engineer specializing in Generative AI and healthcare NLP
Junior Computer Vision Engineer specializing in generative AI and autonomous perception
Richa Chanpuriya
Mid-level Backend/Agentic AI Engineer specializing in GenAI automation and RAG systems
“Built and shipped a production AI-driven privacy automation system that autonomously navigates data broker sites to submit opt-out/data deletion requests end-to-end, including robust CAPTCHA detection/solving (e.g., reCAPTCHA/hCaptcha/Cloudflare) via 2Captcha. Experienced in orchestrating stateful LLM agent workflows with LangGraph and hardening them for production with strict state management, retries/fallbacks, validation layers, and database-backed observability/audit logs, collaborating closely with legal/compliance stakeholders.”