AI Engineer - Healthcare

Mariner

23h•Remote

About The Position

We are seeking experienced AI Engineers to support a public sector healthcare initiative, delivering production-grade AI solutions in a highly regulated environment. This role focuses on real-world impact, building systems that operate within strict privacy, security, and governance frameworks. This is not a research role—you will be responsible for deploying and operationalizing AI in production within an enterprise Azure ecosystem.

Requirements

Proven experience delivering AI/ML solutions in production environments
Hands-on experience with Azure ML / Azure AI (strongly preferred)
Experience working with regulated data environments (healthcare, government, or similar)
Strong understanding of model deployment, monitoring, and lifecycle management
Experience integrating AI into operational systems, not just building models
Ability to work in structured, compliance-driven environments
Always improving your skills and knowledge: you want to be the best at what you do
Curious and creative; comfortable taking on new problems and challenges
A self-starter with the ability to recommend priorities to the project leader
Comfortable working through problems and figuring things out with minimal supervision
Great problem-solving skills: thorough and reliable
Able to work in a team: share knowledge and assist other team members
A good communicator: able to explain your ideas and recommendations
Well organized and dependable under pressure: you manage your time effectively

Nice To Haves

Experience with clinical/NLP data or healthcare analytics
Familiarity with FHIR and healthcare interoperability standards
Exposure to population health, risk modeling, or patient outcomes use cases
Experience implementing GenAI/LLM solutions in secure enterprise environments

Responsibilities

Design, build, and deploy production AI/ML solutions in Azure
Work with Azure ML / Azure AI services across the full lifecycle (training, deployment, monitoring, retraining)
Integrate models into secure enterprise systems (APIs, backend services, data pipelines)
Handle healthcare and regulated data, ensuring compliance with privacy and security standards
Collaborate with data engineers on large-scale data platforms (e.g., Databricks, ETL pipelines)
Implement responsible AI practices, including explainability, bias mitigation, and auditability
Work within public sector delivery structures, engaging with architects, developers, and non-technical stakeholders