Applied AI Engineer

Role overview Take machine learning solutions from early experiments through to reliable production services. You’ll develop and optimize models, build the pipelines and APIs around them, and work with product engineers to integrate AI capabilities into user facing features.

Responsibilities - Train, fine tune, and optimize machine learning models, including large language and open weight models, with attention to quality, latency, and cost. - Build and maintain data, training, and inference pipelines. - Establish model evaluations and quality checks to assess changes before release. - Apply MLOps practices for deployment, monitoring, and automated retraining. - Design and maintain scalable, documented APIs and services for AI features. - Collaborate with backend and frontend engineers to deliver AI in product experiences and improve the supporting infrastructure.

Requirements - Strong core machine learning experience, including taking models from concept to production. - Ability to develop and operate production ML systems and their supporting pipelines. - Experience with Python, cloud services, and modern MLOps practices.