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Vetted FAISS Professionals
Pre-screened and vetted.
Mid-level MLOps Engineer specializing in ML platforms and cloud-native deployment
Mid-level Data Engineer specializing in cloud ETL, streaming, and data warehousing
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
Mid-level Full-Stack Software Engineer specializing in cloud backend and AI infrastructure
Mid-level Data Scientist specializing in LLMs and NLP for financial analytics
Mid-level Data Analyst specializing in ML, AI, and data visualization
Mid-level Data Scientist & AI/ML Engineer specializing in GenAI and LLM-driven enterprise systems
Mid-Level Generative AI Engineer specializing in LLM apps, RAG, and cloud deployment
Senior Data Scientist specializing in NLP, MLOps, and cloud ML platforms
Senior AI Python Engineer specializing in Generative AI and MLOps
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.”
Saikrishna Paila
Junior AI Engineer specializing in RAG pipelines and agentic AI systems
“Built and shipped production RAG/agentic systems in high-stakes domains (biomedical and legal), including an enterprise biomedical document retrieval platform over ~10k scientific docs and a multilingual African-law assistant at the World Bank. Deep hands-on experience with LangChain/LangGraph/LlamaIndex and evaluation tooling (LLM-as-a-judge, safety/hallucination detection), with measurable gains in retrieval quality and hallucination reduction.”
Vamsidhar Vuddagiri
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and MLOps
“Built an LLM-powered academic research assistant for a professor (LangChain + OpenAI + arXiv) focused on synthesizing papers quickly, with emphasis on reliability (ReAct prompting, citation verification) and cost control (caching). Has production MLOps/orchestration experience at Cisco and HCL Tech using Kubernetes, plus MLflow and GitHub Actions for lifecycle management and CI/CD.”