Informacje o stanowisku

technologies-expected :

• Jira
• AI
• Agile

• We are looking for a Scrum Master with strong experience in leading AI/ML projects for our client in the insurance industry. In this role, you will support cross-functional teams of data scientists, ML engineers, and product owners in delivering initiatives based on Generative AI, Computer Vision, and NLP. The position combines core Scrum Master expertise with an understanding of the unique dynamics of machine learning workflows — including model training, data management, and MLOps integration. We are seeking a leader who can remove technical bottlenecks, enhance collaboration between technical and business teams, and foster a culture of experimentation within AI-driven environments.

• Agile Leadership for AI Teams
• Lead sprint planning/retrospectives tailored to AI project cycles:
• Account for model training times, hyperparameter tuning, and data dependencies.
• Manage backlog refinement for AI-specific tasks (e.g., data labeling, A/B testing).
• Resolve AI workflow bottlenecks:
• GPU resource contention, dataset versioning delays, or model validation bottlenecks.
• Coordinate with DevOps for MLOps pipeline integration (CI/CD for models).
• Stakeholder Collaboration
• Bridge technical/non-technical communication:
• Help translate AI model metrics (precision, recall, F1) into business impact for stakeholders.
• Manage expectations around probabilistic AI outputs (e.g., hallucination risks).
• Partner with AI Architects/Data Engineers to:
• Align sprints with cloud resource availability (Azure ML, GCP Vertex AI).
• Track dependencies for multi-team initiatives (e.g., GenAI + data lake teams).
• Process Optimization
• Adapt Scrum/Kanban for AI/ML realities:
• Define “Done” for model iterations (e.g., validation accuracy ≥ 90%).
• Implement hybrid sprints for research (exploratory) vs. deployment phases.
• Introduce tools for AI Agile:
• Jira plug-ins for experiment tracking (MLflow, Weights & Biases).
• Burndown charts accounting for cloud compute costs (Azure/GCP spend).
• Team Enablement
• Coach teams on AI-aware Agile practices:
• Balancing technical debt (legacy models) vs. innovation (LLM prototyping).
• Psychological safety for failed experiments (e.g., model drift issues).
• Foster continuous learning:
• Organize workshops on AI ethics, MLOps, or GenAI trends.
• Share retrospectives across AI teams to propagate best practices.

• Education: Bachelors/Masters in CS or equivalent industry experience (5+ years in ML, 2+ in GenAI).
• Certifications: CSM, PSM, or SAFe Scrum Master.
• Technical Fluency:
• Understanding of AI/ML workflows (model training, validation, deployment).
• Familiarity with tools: Azure DevOps, Jira, MLflow, Databricks.
• Awareness of cloud AI services (Azure ML, GCP Vertex AI, AWS SageMaker).
• Soft Skills:
• Conflict resolution in high-ambiguity AI projects.
• Stakeholder management (C-suite to junior data engineers).

• Work on cutting-edge AI and ML projects in a leading insurance company.
• Have real impact on shaping Agile delivery across AI teams.
• Grow through continuous learning and exposure to modern cloud and MLOps tools.
• A training budget to support your technical and professional development
• Private medical care and co-financing of a sports card
• Flexible working hours and the option to work fully remotely

• sharing the costs of sports activities
• private medical care
• sharing the costs of foreign language classes
• sharing the costs of professional training & courses
• remote work opportunities
• flexible working time
• integration events

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