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Vetted Supervised Learning Professionals
Pre-screened and vetted.
Junior AI/ML Engineer specializing in Responsible AI for healthcare and insurance
Senior Business Analyst specializing in analytics engineering and FinTech data solutions
Mid-level AI/ML Engineer specializing in Generative AI and cloud-based ML systems
Mid-level AI/ML Engineer specializing in LLMs, RAG, and full-stack development
Mid-level Robotics Engineer specializing in autonomous navigation, SLAM, and perception
Mid-level AI/ML Engineer specializing in financial risk, fraud analytics, and MLOps
Mid-level AI Engineer specializing in LLMs, computer vision, and production ML systems
Mid-level Machine Learning Engineer specializing in forecasting, NLP, and MLOps
Mid-level Data Scientist specializing in GenAI, NLP, and cloud MLOps
Senior Data Scientist specializing in ML engineering and cloud analytics
Mid-level AI/ML Engineer specializing in generative AI and cloud ML platforms
Sai Manikanta Kasireddy
Mid-level Machine Learning Engineer specializing in cloud-native GenAI and RAG systems
“Built and productionized an internal GenAI chatbot that makes company policy/SOP knowledge instantly searchable, using a secure RAG architecture on AWS (Bedrock/Titan embeddings/OpenSearch Serverless, Textract/Lambda/S3 ingestion, Claude 3 Sonnet). Demonstrates strong MLOps/orchestration experience (Airflow, Step Functions with Lambda/Glue/SageMaker) and a rigorous reliability approach (RAGAS metrics, A/B testing, citation validation, monitoring), including collaboration with compliance stakeholders via review dashboards.”
Rathi Anand
Senior Full-Stack Software Engineer specializing in Insurance, FinTech, and AI/ML applications
“AI/backend engineer who fine-tuned and deployed a production LLM chatbot using a LangChain + FAISS RAG pipeline, improving latency with PEFT/LoRA and driving strong business impact (40% customer adoption; 92% satisfaction). Also served as technical lead on a data aggregation system for underwriting/quoting, introducing GraphQL for more efficient, maintainable querying and applying CDC to keep cached ranking data fresh at scale.”
Laxminarayana Yaga
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and MLOps
“Built and deployed a production RAG pipeline at PNC Financial Services to let risk/compliance analysts query millions of internal financial documents in natural language, reducing manual search and speeding regulatory validation. Demonstrates deep practical experience with large-scale document ingestion/OCR cleanup, retrieval performance tuning (hierarchical indexing, caching), and LLM reliability controls (grounding, citations, abstention), plus cloud orchestration on Azure and AWS.”
Mid-level AI/ML Engineer specializing in generative AI and MLOps