Czym będziesz się zajmować? Develop and operationalize the ML/AIOps strategy, architecture, and frameworkDefine end-to-end strategy covering classical ML, Generative AI, and Agentic AIAssess existing ML/AI processes, perform gap analyses, and recommend improvementsDesign and implement monitoring, automation, and CI/CD pipelines for ML modelsContribute to model governance, observability, and lifecycle managementProduce clear documentation, reusable assets, and best practicesCollaborate with the Data Scientist in Riga and other business teams (some travel expected)

Kogo poszukujemy? Proven hands-on MLOps experience in production environmentsStrong knowledge of ML pipeline orchestration, e.g., Kubeflow, MLflow, Vertex AI, SageMaker, or similarDeep understanding of model deployment, monitoring, retraining, and drift detectionExperience with containerized and cloud-native infrastructure (Docker, Kubernetes)Proficiency in Python, Git, CI/CD, and infrastructure-as-code toolsFamiliarity with GenAI and LLMOps frameworks (LangChain, Weaviate, vector DBs, etc.)Ability to bridge data science and DevOps disciplines