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Senior Data Scientist
Senior Data ScientistCynet Systems • Redmond, WA, United States
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Senior Data Scientist

Senior Data Scientist

Cynet Systems • Redmond, WA, United States
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  • [job_card.full_time]
[job_card.job_description]

Job Description :

Pay Range : $70hr - $75hr

Responsibilities :

  • Design and implement Agent-to-Agent (A2A) protocols enabling autonomous collaboration, negotiation, and task delegation between specialized AI agents (e.g., ClaimsAgent, EligibilityAgent, ProviderMatchAgent).
  • rchitect and operationalize Model Context Protocol (MCP) pipelines that ensure persistent, memory-augmented, and contextually grounded LLM interactions across multi-turn healthcare use cases.
  • Build intelligent multi-agent systems orchestrated by LLM-driven planning modules to streamline benefit processing, prior authorization, clinical summarization, and member engagement.
  • Fine-tune and integrate domain-specific LLMs and NLP models (e.g., medical BERT, BioGPT) for complex document understanding, intent classification, and personalized plan recommendations.
  • Develop retrieval-augmented generation (RAG) systems and structured context libraries to enable dynamic knowledge grounding across structured (FHIR / ICD-10) and unstructured sources (EHR notes, chat logs).
  • Collaborate with engineers and data architects to build scalable agentic pipelines that are secure, explainable, and compliant with healthcare regulations (HIPAA, CMS, NCQA).
  • Lead research and prototyping in memory-based agent systems, reinforcement learning with human feedback (RLHF), and context-aware task planning.
  • Contribute to production deployment through robust MLOps pipelines for versioning, monitoring, and continuous model improvement.

Required Qualifications :

  • Master's or Ph.D. in Computer Science, Machine Learning, Computational Linguistics, or a related field.
  • 7+ years of experience in applied AI with a focus on LLMs, transformers, agent frameworks, or NLP in healthcare.
  • Hands-on experience with Agent-to-Agent protocols, LangGraph, AutoGen, CrewAI, or similar multi-agent orchestration tools.
  • Practical knowledge and implementation experience of Model Context Protocols (MCP) for long-lived conversational memory and modular agent interactions.
  • Strong coding experience in Python, with proficiency in ML / NLP libraries like Hugging Face Transformers, PyTorch, LangChain, spaCy, etc.
  • Familiarity with healthcare benefit systems, including plan structures, claims data, and eligibility rules.
  • Experience with healthcare data standards like FHIR, HL7, ICD / CPT, X12 EDI formats.
  • Cloud-native development experience on AWS, Azure, or GCP including Kubernetes, Docker, and CI / CD.
  • Preferred Qualifications :

  • Deep understanding of MCP + VectorDB integration for dynamic agent memory and retrieval.
  • Prior work on LLM-based agents in production systems or large-scale healthcare operations.
  • Experience with voice AI, automated care navigation, or AI triage tools.
  • Published research or patents in agent systems, LLM architectures, or contextual AI frameworks.
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