ML & Automation Lead

DCG is a space where business needs and people's ambitions meet. They help candidates find an environment to develop and help companies build effective teams. They work closely with people and organizations, listening carefully and responding to what matters to them, creating lasting and valuable relationships.

• At least 5+ years of experience designing and implementing machine learning, advanced analytics, and process automation solutions
• Experience with ML/AI deployments in at least one public cloud
• Knowledge of modern ML frameworks and analytical tools
• Practical knowledge of MLOps and ML model lifecycle
• Understanding of Responsible AI principles, data ethics, and governance
• Excellent analytical, communication, and presentation skills
• Experience working in agile environments and cross-functional teams
• Bachelor's degree (preferably technical); postgraduate studies or AI/ML certifications are a plus
• Experience in designing AI architectures or Agentic AI is a major asset

Nice to have:

• Cloud
• Advanced Analytics
• RWD
• Team management

• Leading machine learning and process automation projects from concept to production deployment
• Collaborating with clients to identify transformation opportunities using ML, AI, and automation
• Designing and implementing ML models with modern frameworks and analytical tools
• Delivering solutions in cloud environments (Azure, AWS, others) focusing on scalability and reliability
• Applying MLOps practices including model monitoring, retraining, deployment, and governance
• Ensuring compliance with Responsible AI principles, data ethics, and privacy protection
• 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
• Co-creating 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 architecture and estimates
• Monitoring market and technology trends (ML, GenAI, Agentic AI, automation)
• Knowledge sharing and internal/external thought leadership