Role Purpose:• Drive the overall MLOps strategy along with other members of the Data Science & Insights (DS&I) team, while also collaborating with senior leadership to align strategies with broader organizational goals and objectives• Lead the development of innovative software tools to service both our Data Science solutions and wider business operations using relevant cutting-edge technologies (e.g. AWS, Git, Docker, Kubernetes, Jenkins)• Ensure the architecture is continuously improved and evaluate emerging technologies and trends to maintain a competitive edge in the market• Lead the development of tools/services that support critical operations such as release management, source code management, CI/CD pipelines, automation, serving ML models to production environments and many other key operations while also overseeing the integration of these solutions into our broader technology ecosystem.• Champion ML model-governance by establishing full end-to-end lifecycle governance framework to ensure models are monitored, refreshed and performing at optimal levels over time.• Collaborate closely with key stakeholders across various business functions, including Product & Technology (P&T), IT, and Developer Experience (DX) teams, to develop and prioritize a strategic Data Science DevOps roadmap that aligns with organizational objectives and drives innovation.• Mentor and coach team members, providing guidance, support, and expertise on advanced MLOps practices, while also serving as a point of escalation for complex technical challenges and issuesReporting to: Director of Data Science & InsightsKey Skills Required:• M.S. or Ph.D. in a relevant technical field, or 5+ years’ experience in a relevant role.• Solid understanding of DevOps practices or full-stack software engineering in general• Some experience of leading a team or keen interest in becoming a People Manager along with strong ability to coach high-performing DevOps Engineers• Expertise in writing production-level Python code• Expertise in cloud computing service like AWS, Google Cloud,etc.• Expertise in Containerisation technologies like Docker, Kubernetes,etc.• Expertise in software engineering practices: design pattern, data structure, object oriented programming, version control, QA, logging & monitoring,etc.• Expertise in writing unit tests and developing integration tests to ensure quality of the product• Experience and knowledge of Infrastructure as Code best practices• Experience in developing GenAI tools seen as a plus• Knowledge of leading cross-function projects and R&D projects• Knowledge of agile project managementCompany:CarTrawlerQualifications:Language requirements:Specific requirements:Educational level:Level of experience (years):Senior (5+ years of experience)Tagged as: Industry, Ireland, Machine Learning, NLP, QA
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