Senior ML / LLM Engineer (No sponsorship provided)
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
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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
Apply tot his job
Apply To this Job