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Vetted Model Evaluation Professionals
Pre-screened and vetted.
Senior AI/ML Research Engineer specializing in cybersecurity and graph neural networks
Mid-level AI/ML Researcher specializing in LLMs, conversational agents, and health NLP
Mid-level AI/ML Engineer specializing in GenAI, NLP, and AWS MLOps
Mid-level AI & Machine Learning Engineer specializing in MLOps and NLP
Mid-level Data Analyst/Data Scientist specializing in ML, dashboards, and predictive analytics
Senior Software Engineer specializing in AI-first architectures, RAG systems, and zero-trust security
Mid-Level Full-Stack Software Engineer specializing in cloud-native web platforms and ML evaluation
Mid-level Data Engineer specializing in Python/SQL ETL pipelines and analytics enablement
Mid-Level AI Engineer specializing in LLM systems, GPU optimization, and multi-agent orchestration
Mid-level AI/ML Engineer specializing in LLM, RAG, and agentic systems
Mid-level Data Analyst/Data Engineer specializing in machine learning and NLP
Junior AI Engineer specializing in distributed ML pipelines and time-series forecasting
Mid-level Software Development Engineer specializing in Java microservices and FinTech
Junior Machine Learning Engineer specializing in healthcare AI and GenAI RAG
Shreevershith Kollabettu
Mid-level AI Engineer specializing in LLMs, agentic systems, and MLOps
“AI-focused engineer with Infosys experience building Azure/.NET chatbot applications and recent hands-on work with FastAPI/LangChain. Built a hackathon multi-agent legal counsel system showcasing agent orchestration, and emphasizes production readiness via Docker, GitHub Actions CI/CD, pytest automation, and adversarial simulations for auditable AI behavior. No direct robotics/ROS experience to date.”
revanth polthi
Mid-level Data Scientist specializing in Generative AI and MLOps
“GenAI/LLM engineer with production experience at Allstate building an end-to-end document intelligence workflow for insurance operations—automating document intake, classification, and risk signal extraction. Emphasizes high-reliability design for regulated/high-stakes outputs using schema enforcement, confidence thresholds, validation rules, and human-in-the-loop routing, with metric-driven offline evaluation and production monitoring.”
Senior Technical Customer Success Manager specializing in enterprise telecom and video delivery
Intern Software Engineer specializing in AI/ML and data-driven web tools
Mid-level Machine Learning Engineer specializing in healthcare and enterprise analytics
Sravani Gangaraju
Mid-level AI/ML Engineer specializing in NLP, computer vision, and recommender systems
“Built and deployed a production NLP sentiment analysis system at Piper Sandler to turn noisy, finance-specific customer feedback into scalable insights. Demonstrates strong end-to-end MLOps: fine-tuning BERT, improving label quality, monitoring for language drift, and automating retraining/deployment with Airflow and Docker (plus Kubeflow exposure).”
Mahesh Ponnam
Mid-level Data Scientist specializing in credit risk, fraud detection, and ESG analytics
“AI/LLM practitioner who has deployed production chatbots across e-commerce, HRMS, and real estate, focusing on retrieval-first workflows for factual tasks like product and property search. Optimized intent understanding and significantly improved latency by using lightweight embeddings and tuning the inference pipeline on Groq (Llama 3.3), while applying modular orchestration and measurable production evaluation.”
Hemant Deshmukh
Mid-level Data Engineer specializing in cloud data pipelines and analytics engineering
“Built and deployed a production LLM-powered demand and churn forecasting system for an e-commerce client, combining open-source LLMs (LLaMA/Mistral) and Sentence-BERT embeddings to generate business-friendly explanations of forecast drivers. Strong focus on data quality and model trust (validation, baselines, segmented monitoring) and production reliability via Airflow-orchestrated pipelines with readiness checks, retries, and ongoing drift/A-B testing.”