Teams at Twoday

Build, deploy, and operate production machine learning and generative AI systems for customers. Responsibilities include developing training and inference pipelines, model serving, monitoring, alerting, retraining, MLOps automation, RAG solutions, governance, and AI evaluation. The role involves close collaboration with customer technical teams, code reviews, knowledge sharing, and mentoring, with opportunities to progress toward technical leadership.

Develop and productionize predictive and generative AI models for customer business problems. Responsibilities include problem framing, feature engineering, algorithm selection, statistical validation, model documentation, evaluation metrics, production collaboration, governance, stakeholder presentations, code reviews, and mentoring. The role works closely with data engineers, AI/ML engineers, cloud architects, software developers, analysts, and domain experts across customer projects.

Leads the architecture, engineering, deployment, and operation of production ML and generative AI systems. Owns MLOps platforms, training and inference pipelines, model and prompt lifecycles, monitoring, governance, and automated retraining. Establishes engineering standards, advises customers, mentors engineers and data scientists, supports AI presales, evaluates emerging tools, and represents the company’s AI/ML capabilities. Strong software engineering, Azure, infrastructure-as-code, containers, Kubernetes, RAG, and Danish communication skills are required.