ML & Automation Manager

At least 5+ years of experience in designing and implementing solutions in the areas of machine learning, advanced analytics, and process automationExperience with ML/AI deployments in at least one public cloudKnowledge of modern ML frameworks and analytical toolsPractical knowledge of MLOps and the ML model lifecycleUnderstanding of Responsible AI principles, data ethics, and governanceExcellent analytical, communication, and presentation skillsExperience with project work in an agile environment and cross-functional teamsBachelor's degree (preferably in a technical field); postgraduate studies or AI/ML certifications are a plusExperience in designing AI architectures or Agentic AI – a major asset ,[Leading machine learning and process automation projects from the concept phase through to production deployment, Collaborating with clients to identify areas with high potential for transformation using ML, AI, and automation, Designing and implementing ML models using modern frameworks and analytical tools, Delivering solutions in cloud environments (Azure, AWS, others) with a focus on scalability and reliability, Applying MLOps practices (model monitoring, retraining, deployment, governance), Ensuring solutions comply with Responsible AI principles, data ethics, and privacy protection, Clearly communicating analysis results and recommendations to business and technical stakeholders, Managing, mentoring, and developing teams of ML engineers and automation specialists, Ensuring high-quality project deliverables and timely completion of objectives, Co-creating the ML & Automation competency development strategy within the Data & AI team, Building and developing a repository of reusable assets, accelerators, and architectural patterns, Providing technical input for proposals, offers, and presales, including defining architecture and estimates, Monitoring market and technology trends (ML, GenAI, Agentic AI, automation), Knowledge sharing – internal and external thought leadership] Requirements: Machine learning, AWS, Cloud, AI, Azure, GenAI Additionally: Sport subscription, Private healthcare.