Production AI/LLMOps Engineer for Healthcare

DKAI Tech; EE. UU.; A distancia; USD 130.000 - 195.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Healthcare AI experience

Descripción de la vacante

DKAI Tech is seeking an AI/ML Engineer to build production systems using generative AI, deep learning, large language models, and cloud AI services in healthcare solutions. You will operationalize models, create reliable pipelines, and implement deployment processes for real-world use.

The role combines advanced Python engineering with MLOps, infrastructure, governance, and cross-team enablement, supporting security and ethical-use practices while improving efficiency across teams.

Formación

• Minimum of 1 year in MLOps/LLMOps.
• Strong software engineering with Python.
• Experience with cloud-based services and multi-cloud environments.
• Understanding of infra needs for operating LLM systems.
• Ability to lead knowledge-sharing sessions.

Responsabilidades

• Design and maintain LLM pipelines for training, fine-tuning, eval, deployment.
• Scale LLM apps from experiments to production with repeatable processes.
• Implement monitoring and observability for latency, throughput, and model behavior.
• Manage prompt versioning and retrieval-augmented generation workflows.
• Automate model validation, testing, and CI/CD for safe releases.
• Apply security, governance, and ethical-use practices to production LLMs.
• Review processes to improve efficiency and enable cross-team collaboration.

Conocimientos

Advanced Python

MLOps/LLMOps

Cloud services

LLM infrastructure

Production ML frameworks

Educación

Bachelor's or Master's degree

Descripción del empleo

DKAI Tech is seeking an AI/ML Engineer to build production systems using generative AI, deep learning, large language models, and cloud AI services in healthcare solutions. You will operationalize models, create reliable pipelines, and implement deployment processes for real-world use.

The role combines advanced Python engineering with MLOps, infrastructure, governance, and cross-team enablement, supporting security and ethical-use practices while improving efficiency across teams.