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Vetted BERT Professionals
Pre-screened and vetted.
Junior Data Scientist specializing in risk modeling, NLP, and predictive analytics
Mid-level Data Scientist specializing in LLMs and NLP for financial analytics
Mid-level Data Scientist specializing in NLP, time-series forecasting, and GenAI
Senior Data Engineer specializing in real-time pipelines, cloud data platforms, and healthcare analytics
Senior AI/ML & Data Science professional specializing in NLP, LLMs, and MLOps
Mid-level AI/ML Engineer specializing in MLOps, NLP/CV, and fraud detection
Senior AI/ML Engineer specializing in LLMs, NLP, and production MLOps
Mid-level Data Scientist specializing in ML, NLP, and cloud deployment
Asvad Shaik
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and NLP
“Backend engineer who built and migrated a large-scale document intelligence platform used by legal, healthcare, and insurance clients, processing millions of pages. Experienced moving from a monolithic, LLM-heavy approach to a modular FastAPI service architecture with ML classification + RAG, strong validation/auditability, and enterprise security (JWT/OAuth, RBAC, PostgreSQL RLS) with zero-downtime incremental rollouts.”
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.”