Senior AI/ML Engineer - Applications & Automation
$150k - $200k/yr
Senior
Remote in USA+3 moreMore locations: Houston, TX, USA | Rosemont, IL, USA | Chicago, IL, USA
Remote
Software EngineeringAI Application Engineering
About the job
Requirements
- At least 5 years of experience 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 retrieval-augmented generation solutions, including embeddings, vector databases, semantic search, and context engineering.
- Hands-on MLOps experience taking models and agents into production, including 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.
- Troubleshooting and root-cause analysis skills, and ability to partner with domain experts and convert ambiguous workflow needs into scalable technical solutions.
- Clear written and verbal communication in cross-functional environments.
Responsibilities
- Develop machine learning models, agents, and automation workflows for terminology management, content creation, mapping, and validation, evolving them from experimentation into scalable production systems.
- Build agentic workflows that use large language models, tools, APIs, knowledge sources, retrieval capabilities, and structured business rules to complete complex tasks.
- Build and maintain retrieval-augmented generation solutions, vector and semantic search capabilities, and prompt and context-management strategies.
- Partner with the data science team to understand, integrate, and productionize existing agents, and contribute model and agent development to the team's roadmap.
- Own deployment, monitoring, troubleshooting, and continuous improvement of AI workflows in production, including root-cause analysis and durable remediation of failures or unexpected outputs.
- Design evaluation, testing, and observability practices for AI systems, and implement controls for auditability, explainability, and human-in-the-loop review in clinically sensitive workflows.
- Develop cloud-based solutions using AWS services such as Amazon Bedrock, SageMaker, and Lambda, applying CI/CD, containerization, automated testing, and secure development practices.
- Work with clinical, mapping, product, data science, and engineering partners to translate workflows into practical solutions and define where AI automation, deterministic logic, and human review are appropriate.
Desired Qualifications
- Experience with LangChain or LangGraph, LlamaIndex, OpenSearch, vector databases, or evaluation frameworks.
- Experience with multi-agent or tool-using workflows, including state management, memory, routing, and failure recovery.
- Experience with testing and evaluation approaches for non-deterministic AI systems.
- Experience in 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.
- Experience with AI solutions incorporating human review, auditability, explainability, and quality governance.
About the company
IMO Health provides healthcare data enablement by licensing and managing medical vocabularies and clinical data tools that ensure data integrity and quality. Its clinical data intelligence solutions organize point-of-care information using comprehensive medical terminology and AI, and are embedded in EHR systems and other healthcare applications. This helps clinicians have clearer problem lists, streamlined charting, better patient documentation, and improved data analytics. The company differentiates itself by focusing on authoritative vocabularies and standardized data to ensure consistent, machine-readable information across care settings, serving hospitals, clinics, and other providers through partnerships with medical societies and government entities, with the goal of improving clinician experience, billing efficiency, and smart clinical decisions.
Company Size
501-1,000
Company Stage
N/A
Total Funding
N/A
Headquarters
Harrisburg, Pennsylvania
Founded
1994
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Simplify's Take
What believers are saying
- April 28, 2026 Knowledge Graph access targets healthcare AI developer demand.
- July 28, 2026 Modular Medical expands IMO into diabetes patient identification workflows.
- May 7, 2026 MedTech Breakthrough recognition strengthens buyer trust in IMO’s data layer.
What critics are saying
- THL ownership increases pressure for rapid growth, margins, and eventual exit.
- Epic, Oracle, and MEDITECH can bundle terminology, crushing standalone pricing power.
- If EHRs and AI platforms internalize terminology, IMO becomes a feature, not a company.
What makes IMO Health unique
- IMO Health integrates across Epic, Oracle, MEDITECH, and NextGen workflows.
- Its knowledge graph reaches 4,500+ provider organizations and 90% of U.S. clinicians.
- GraphQL and MCP access expose clinical context for AI agents without custom ontologies.
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Benefits
- Hybrid Work Options