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 issues
Reporting to: Director of Data Science & Insights
Key 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 management
Company:
CarTrawler
Qualifications:
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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