Remote job
AI / ML Engineer
Job details
About this role
Role overview
This AI/ML Engineer role focuses on building production systems that use generative AI, deep learning, large language models, and cloud AI services in healthcare solutions. You will take models and experiments through operationalization, creating reliable pipelines, evaluation practices, observability, and deployment processes for real-world use. The role combines advanced Python engineering with MLOps/LLMOps, infrastructure, security, governance, and cross-team enablement.
Responsibilities
- Design, build, and maintain LLM pipelines for training, fine-tuning, evaluation, and deployment. - Move LLM applications from experimentation into production environments with repeatable operational processes. - Implement monitoring and observability for latency, throughput, model behavior, hallucinations, and related quality signals. - Manage prompt versioning, fine-tuning workflows, and retrieval-augmented generation systems. - Automate model validation, testing, and CI/CD pipelines to support safe and dependable releases. - Apply security, data governance, compliance, and ethical-use practices to production LLM systems. - Review existing processes, improve efficiency, and provide solutions that help multiple teams work effectively.
Requirements
- At least one year of experience in MLOps or LLMOps. - Strong software engineering background with advanced Python skills. - Thorough understanding of infrastructure requirements for operating LLM systems. - Experience with cloud-based services, including multi-cloud environments and AI services. - Familiarity with machine learning frameworks and techniques for optimizing models in production. - Strong problem-solving skills and the ability to lead or facilitate knowledge-sharing sessions. - Bachelor’s or master’s degree, or equivalent education; the source specifies 15 years of full-time education.
Nice to have
- Experience designing production-grade healthcare AI systems where reliability, governance, privacy, and responsible use are central considerations.