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Vetted Classification Professionals
Pre-screened and vetted.
Junior Data Analyst specializing in ML, analytics engineering, and data visualization
Mid-level ML Engineer specializing in LLMs, document AI, and computer vision
Senior Machine Learning Scientist specializing in forecasting, optimization, and agentic LLM systems
Junior Machine Learning Engineer specializing in fraud detection, KYC, and LLM applications
Junior Data Scientist specializing in machine learning and analytics
Mid-Level Full-Stack Software Engineer specializing in cloud, microservices, and AI/LLM systems
Mid-level AI Engineer specializing in NLP, LLM fine-tuning, and RAG systems
Senior Data Scientist and ML Engineer specializing in NLP, LLMs, and AI systems
Mid-level AI Software Engineer specializing in LLMs and healthcare AI
Mid-level Applied AI Engineer specializing in LLMs, Prompt Engineering, and RAG
Junior Full-Stack & ML Engineer specializing in AI-powered web products
Mid-level AI/ML Engineer specializing in cloud AI, MLOps, and NLP
Mid-level Data Analyst specializing in marketing analytics and machine learning
Swarag Reddy Pingili
Junior AI/ML Software Engineer specializing in LLM agents and RAG systems
“AI/back-end engineer at Canon who helped build and operate an internal production LLM platform that acts as a secure middle layer between users and models, defending against jailbreaks/prompt injection while enabling RAG, memory, and grounded responses over company data. Experienced with LangChain/LangGraph orchestration, vector DB retrieval, and reliability practices (testing, monitoring, adversarial prompts) to run high-throughput, low-latency AI workflows in production.”
Maneesh Ujji
Junior Machine Learning & Data Science professional specializing in AI agents and applied ML
“IT Analyst/research background with hands-on experience deploying and hardening a multi-agent AI support/triage system (ticket ingestion + knowledge-base retrieval) with strong emphasis on reliability and observability. Has debugged real production issues spanning backend services and network latency (sync failures/partial writes) and is comfortable in Linux environments; also has academic exposure to robotics simulation and ROS2.”
Helly Shah
Junior Data Analyst specializing in business analytics and machine learning
“Analytics-focused candidate with hands-on project experience in SQL data preparation and Python-based churn modeling. They demonstrated a practical approach to turning messy multi-source data into reporting tables, validating data quality rigorously, and translating churn insights into targeted retention strategies.”
Ainesh Gunturu
Junior Data Analyst specializing in marketing analytics and machine learning
“Built and deployed a production LLM-assisted recommendation and insights platform that unifies structured, semi-structured, and unstructured data via a modular ingestion pipeline, canonical schemas, embeddings, and late-fusion modeling. Experienced in operationalizing ML/LLM systems with Airflow and Kubernetes (Dockerized services, autoscaling, rolling updates) and emphasizes reliability through layered testing, guardrails, monitoring, and A/B experimentation while partnering closely with non-technical stakeholders.”
Nikhitha Todeti
Mid-level AI Engineer specializing in ML, LLM applications, and data automation
“Data/ML practitioner who has built a production RAG-based knowledge assistant integrated into Microsoft 365/internal dashboards to help employees query internal documents in plain English. Experienced orchestrating and hardening ETL pipelines with Airflow and Azure Data Factory (validation, retries, monitoring) and running end-to-end model evaluation and production performance tracking via Power BI.”