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The Senior AI/ML Engineer will design, build, and deploy AI models and agentic workflows for clinical terminology and content operations. This role involves owning the production lifecycle, including monitoring, troubleshooting, and implementing observability practices for AI systems.
We are seeking a Senior AI/ML Engineer to design, build, deploy, and evolve AI models, agents, and workflow automation for clinical terminology and content operations. This hands-on role combines AI/ML development with production ownership, taking models and agents from experimentation to reliable production use. The ideal candidate has experience with large language models, agent frameworks, retrieval-augmented generation, and the infrastructure and controls required to operate AI systems reliably.
\n5+ years across AI/ML engineering, data science, machine learning engineering, or related disciplines, with a foundation in applied machine learning.
Hands-on experience building agents and agentic workflows, including orchestration and tool or function calling.
Hands-on experience building RAG solutions, including embeddings, vector databases, semantic search, and context engineering.
Hands-on MLOps experience taking models and agents into production — deployment, versioning, monitoring, and CI/CD across multiple environments.
Strong Python proficiency and experience developing maintainable services, APIs, pipelines, or workflow automation, plus working knowledge of SQL and relational databases such as PostgreSQL.
Experience with cloud-based AI infrastructure, preferably AWS and Amazon Bedrock.
Strong troubleshooting and root-cause analysis skills, and the ability to partner with domain experts and convert ambiguous workflow needs into scalable technical solutions.
Clear written and verbal communication in cross-functional environments.
LangChain or LangGraph, LlamaIndex, OpenSearch, vector databases, or evaluation frameworks.
Multi-agent or tool-using workflows, including state management, memory, routing, and failure recovery.
Testing and evaluation approaches for non-deterministic AI systems.
Healthcare technology, clinical terminology, clinical data normalization, mapping workflows, or regulated data environments.
Familiarity with healthcare data standards such as knowledge graphs, FHIR, SNOMED CT, LOINC, RxNorm, ICD-10, or CPT.
AI solutions incorporating human review, auditability, explainability, and quality governance.
Compensation at IMO Health is determined by job level, role requirements, and each candidate’s experience, skills, and location. The listed base pay represents the target for new hires with individual compensation varying accordingly. These figures exclude potential bonuses, equity, or sales incentives, which may also be part of the total compensation package. Our recruiter will provide additional details during the hiring process.
IMO Health also offers a comprehensive benefits package. To learn more, please visit IMO Health's Careers Page.
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