Scrum Master

You will be working as a Scrum Master at Dailoqa, where you'll play a crucial role in bridging agile practices with the unique requirements of AI/ML-driven product development. Your responsibilities will involve coaching cross-functional teams of software engineers, data scientists, and ML engineers to deliver impactful solutions while promoting a culture of collaboration, experimentation, and continuous improvement. **Key Responsibilities:** - **Agile Facilitation & Coaching** - Facilitate all Scrum ceremonies with a focus on outcomes rather than outputs. - Coach team members on Agile principles, ensuring adherence to Scrum frameworks while adapting practices to AI/ML workflows. - **Sprint & Workflow Management** - Manage hybrid sprints encompassing software development, data science research, and ML model training/deployment. - Maintain Agile boards to provide real-time progress updates and ensure transparency for stakeholders. - Monitor sprint velocity, burndown charts, and cycle times to identify bottlenecks and enhance predictability. - **AI/ML-Specific Agile Leadership** - Adapt Agile practices to AI/ML challenges by advocating for experimentation, embracing uncertainty, and resolving dependencies between different teams. - **Continuous Improvement** - Lead retrospectives focusing on technical and process enhancements. - Drive the adoption of Agile engineering practices tailored to AI/ML workflows. **Qualifications (Must-Have):** - 5-8 years of experience as a Scrum Master, with 2+ years supporting AI/ML or data science teams. - Deep understanding of Agile frameworks (Scrum, Kanban) and tools (Jira, Azure DevOps). - Proven ability to coach teams through AI/ML-specific challenges such as model lifecycle management and balancing research-heavy work with delivery timelines. - Certifications like CSM, PSM, or equivalent. - Strong grasp of Agile frameworks and SDLC principles. - Experience collaborating with cross-functional teams, including data scientists and AI engineers. - Exposure to AI/ML product development cycles and elements like model training, data labeling, GenAI experimentation, or MLOps.,