.png){kind=logo}
Vetted Model Monitoring Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in NLP and MLOps for regulated industries
Senior Data Scientist specializing in Generative AI, NLP, and ML for banking and healthcare
Junior Data Scientist specializing in risk modeling, NLP, and predictive analytics
Mid-level AI/ML Engineer specializing in financial risk, fraud detection, and NLP
Senior Data Scientist specializing in AWS ML solutions for healthcare, telecom, and e-commerce
Senior AI/ML & Data Science professional specializing in NLP, LLMs, and MLOps
Senior AI/ML Engineer specializing in LLMs, NLP, and production MLOps
Mid-Level Generative AI Engineer specializing in LLM apps, RAG, and cloud deployment
Mid-level AI Engineer specializing in production LLM, RAG, and agentic AI systems
Rahul Manne
Mid-Level Software Engineer specializing in .NET, Azure, and ML automation
“JavaScript/React/TypeScript engineer with hands-on open-source experience improving a hooks utility library—fixed a reported async race condition that reduced unexpected re-renders and added a debounced callback hook that became widely used. Brings a production-minded approach to performance and abstractions (APM/metrics-driven, DB/caching focus) with strong testing, documentation, and community support practices.”
vedavathi thumula
Mid-level GenAI/ML Engineer specializing in agentic AI and RAG systems
“Backend/platform engineer who has owned a Python/FastAPI results API and deployed it on Kubernetes with Helm and GitHub Actions-driven CI/CD. Demonstrates strong production operations mindset across performance tuning, monitoring, safe rollouts/rollbacks, and phased migrations, plus hands-on Kafka streaming experience focused on ordering and idempotency.”
Pravallika Kilari
Mid-level AI/ML Engineer specializing in NLP, GenAI, and MLOps in healthcare and finance
“AI/ML engineer with CVS Health experience deploying production LLM systems in regulated healthcare settings, including a large-scale RAG solution (1M+ documents) built for compliance-grade, auditable policy/regulatory Q&A with strong anti-hallucination controls. Also delivered an NLP summarization system for physician notes/case narratives by partnering closely with non-technical care operations stakeholders and iterating via prototypes, dashboards, and feedback loops.”
Chandan Chalumuri
Mid-level Data Scientist specializing in ML, NLP, and Generative AI
“Data engineering / ML practitioner with experience at MetLife building transformer-based sentiment analysis over large unstructured datasets and productionizing pipelines with Airflow/PySpark/Hadoop (reported 52% efficiency gain). Also implemented embedding-based semantic search using Pinecone/Weaviate to improve retrieval relevance and enable RAG for customer support and document matching use cases.”