Senior ML / LLM Engineer (No sponsorship provided)
recruit22 LLC, Nashville, TN, United States
recruit22 is conducting a search on behalf of a client in the healthcare and clinical technology space. Our client is expanding its Clinical Intelligence and Workflow Automation capabilities to support clinicians, reduce administrative burden, and improve patient outcomes.
We are seeking a Senior ML / LLM Engineer to design and implement production-grade AI systems that enable intelligent decision support, workflow automation, and real-time clinical insights. This role is highly hands-on and focuses on agentic AI systems, Retrieval-Augmented Generation (RAG) pipelines, and scalable ML infrastructure integrated into enterprise platforms and clinical workflows.
Location:
United States
Employment Type:
Full-Time, Exempt
Salary Range:
$155,000 - $165,000 base salary
(compensation may vary based on experience and location)
Visa Sponsorship:
Not available at this time
Key Responsibilities
Design and implement AI agent systems using frameworks such as LangGraph, Semantic Kernel, or custom orchestration layers
Build and maintain RAG pipelines grounded in structured data, domain-specific guidelines, and real-time signals
Develop AI systems that synthesize fragmented data (structured, semi-structured, and unstructured) into prioritized, actionable insights
rchitect and operate scalable, low-latency inference services suitable for production environments
Build evaluation and validation frameworks to ensure AI outputs are accurate, reliable, unbiased, and aligned with source-of-truth data
Implement and manage vector search infrastructure using technologies such as Pinecone, Milvus, Weaviate, or similar platforms
Perform model fine-tuning, PEFT/LoRA training, and optimization for production workloads
Develop high-performance backend services in C#/.NET to integrate AI systems with existing enterprise platforms
Ensure AI solutions comply with data privacy, security, and regulatory standards (HIPAA experience is a strong plus)
Research and evaluate emerging AI technologies to continuously improve system performance and user impact
Mentor junior engineers and act as a technical leader on critical initiatives
Participate in code reviews and contribute to consistent engineering standards
Collaborate cross-functionally with product, clinical, and engineering stakeholders to translate workflows into intelligent systems
Required Qualifications
Bachelor's degree preferred
5+ years of professional experience in ML/LLM engineering with production-grade systems
Deep experience with LLM orchestration, tool calling, and long-context document handling
Strong proficiency with vector databases (e.g., Pinecone, Milvus, Weaviate)
Hands-on experience with MLOps practices including Docker, Kubernetes, CI/CD, and deployment pipelines
Strong proficiency with C#/.NET for backend service development
Experience designing scalable, low-latency inference systems
Strong understanding of data modeling and workflow mapping
Experience building automated tests and AI evaluation frameworks
Proficiency with version control tools such as Git / Azure DevOps
Experience using JIRA or similar tools for task tracking
Strong analytical thinking and problem-solving skills
Experience with modern AI development tools (e.g., Copilot, Cursor)
Nice-to-Have Qualifications
Healthcare, EHR, claims, or clinical data domain experience
Familiarity with healthcare interoperability standards such as FHIR or HL7
Experience working in regulated environments with PHI
We are seeking a Senior ML / LLM Engineer to design and implement production-grade AI systems that enable intelligent decision support, workflow automation, and real-time clinical insights. This role is highly hands-on and focuses on agentic AI systems, Retrieval-Augmented Generation (RAG) pipelines, and scalable ML infrastructure integrated into enterprise platforms and clinical workflows.
Location:
United States
Employment Type:
Full-Time, Exempt
Salary Range:
$155,000 - $165,000 base salary
(compensation may vary based on experience and location)
Visa Sponsorship:
Not available at this time
Key Responsibilities
Design and implement AI agent systems using frameworks such as LangGraph, Semantic Kernel, or custom orchestration layers
Build and maintain RAG pipelines grounded in structured data, domain-specific guidelines, and real-time signals
Develop AI systems that synthesize fragmented data (structured, semi-structured, and unstructured) into prioritized, actionable insights
rchitect and operate scalable, low-latency inference services suitable for production environments
Build evaluation and validation frameworks to ensure AI outputs are accurate, reliable, unbiased, and aligned with source-of-truth data
Implement and manage vector search infrastructure using technologies such as Pinecone, Milvus, Weaviate, or similar platforms
Perform model fine-tuning, PEFT/LoRA training, and optimization for production workloads
Develop high-performance backend services in C#/.NET to integrate AI systems with existing enterprise platforms
Ensure AI solutions comply with data privacy, security, and regulatory standards (HIPAA experience is a strong plus)
Research and evaluate emerging AI technologies to continuously improve system performance and user impact
Mentor junior engineers and act as a technical leader on critical initiatives
Participate in code reviews and contribute to consistent engineering standards
Collaborate cross-functionally with product, clinical, and engineering stakeholders to translate workflows into intelligent systems
Required Qualifications
Bachelor's degree preferred
5+ years of professional experience in ML/LLM engineering with production-grade systems
Deep experience with LLM orchestration, tool calling, and long-context document handling
Strong proficiency with vector databases (e.g., Pinecone, Milvus, Weaviate)
Hands-on experience with MLOps practices including Docker, Kubernetes, CI/CD, and deployment pipelines
Strong proficiency with C#/.NET for backend service development
Experience designing scalable, low-latency inference systems
Strong understanding of data modeling and workflow mapping
Experience building automated tests and AI evaluation frameworks
Proficiency with version control tools such as Git / Azure DevOps
Experience using JIRA or similar tools for task tracking
Strong analytical thinking and problem-solving skills
Experience with modern AI development tools (e.g., Copilot, Cursor)
Nice-to-Have Qualifications
Healthcare, EHR, claims, or clinical data domain experience
Familiarity with healthcare interoperability standards such as FHIR or HL7
Experience working in regulated environments with PHI