C2C- Data Scientist-AI/ML - Woodland Hills, CA (Hybrid) - Healthcare Domain (FHIR) is must

Hi,



I hope this email finds you well.



My name is Arjun and I am a Technical Recruiter from Empower
Professionals Inc. I came across your profile and wanted to reach out
regarding a Data Scientist role with one of our clients based in
Woodland Hills, CA (Hybrid). Please let me know if you are available in
the job market and interested in this role (see job description below) -
if so, we can connect and speak further.



I would need your updated resume to proceed and can give you a call as
soon as I have it.


Healthcare data standards like FHIR, HL7, ICD/CPT, X12 EDI formats.
AI/ML
Role: Data Scientist
Location: Woodland Hills, CA (Hybrid)
Duration: 12+ Months



Must have:

AI agent architectures, LLMs, NLP developing A2A Protocols and Model
Context Protocols (MCP)

LLMs and NLP models (e.g., medical BERT, BioGPT)

Retrieval-augmented generation (RAG)

Coding experience in Python, with proficiency in ML/NLP libraries

Healthcare data standards like FHIR, HL7, ICD/CPT, X12 EDI formats.

AWS, Azure, or GCP including Kubernetes, Docker, and CI/CD



We are seeking a Senior Data Scientist with deep expertise in LLMs, NLP,
and agent architectures to lead the development of interoperable,
self-improving AI agents in the healthcare domain. This role focuses on
designing advanced multi-agent systems that interact intelligently
across clinical, administrative, and benefits platforms using
Agent-to-Agent (A2A) protocols and Model Context Protocols (MCP).



Responsibilities:

Design and implement A2A protocols for autonomous task delegation and
collaboration among specialized AI agents (e.g., ClaimsAgent,
ProviderMatchAgent).

Develop MCP pipelines to enable persistent memory and context continuity
across multi-turn healthcare interactions.

Architect and deploy LLM-orchestrated agent systems for use cases like
prior authorizations, benefit optimization, and clinical summarization.

Fine-tune domain-specific LLMs and NLP models (e.g., medical BERT,
BioGPT) for intent classification and personalized recommendations.

Build retrieval-augmented generation (RAG) systems with
structured/unstructured healthcare data (e.g., FHIR, ICD-10, EHR).

Collaborate on building scalable, secure, and compliant ML pipelines
(HIPAA, CMS, NCQA).

Lead research in memory-based agents, RLHF, and context-aware planning.

Contribute to end-to-end MLOps pipelines for deployment, monitoring, and
iteration.



Required Qualifications:

Master's/Ph.D. in CS, ML, NLP, or related field.

7+ years in applied AI, particularly with LLMs, transformers, or agent
systems in healthcare.

Proficiency with tools like LangGraph, AutoGen, CrewAI, and hands-on A2A
protocol development.

Proven experience with Model Context Protocols, LLM pipelines, and
healthcare NLP.

Strong Python skills with libraries such as Hugging Face, LangChain,
spaCy, and PyTorch.

Understanding of healthcare systems (e.g., claims, eligibility, plan
design).

Experience with healthcare data standards: FHIR, ICD/CPT, HL7, X12 EDI.

Cloud-native development: AWS/GCP/Azure, Docker/Kubernetes, CI/CD.



Preferred Qualifications:

Expertise in MCP + VectorDB for agent memory and dynamic context
retrieval.

Experience building production-grade LLM agents in healthcare.

Background in voice AI, AI navigation, or triage systems.

Published work or patents in LLM-based agent systems or contextual AI.



Awaiting your quick response. Thanks!



Thanks
Arjun Singh Shekhawat
Technical Recruiter| Empower Professionals
......................................................................................................................................
arjun@empowerprofessionals.com |
LinkedIn: https://www.linkedin.com/in/arjun-singh-shekhawat-681bb3238/
100 Franklin Square Drive – Suite 104 | Somerset, NJ 08873
www.empowerprofessionals.com
Certified NJ and NY Minority Business Enterprise (NMSDC)

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