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 generalSome experience of leading a team or keen interest in becoming a People Manager along with strong ability to coach high-performing DevOps EngineersExpertise in writing production-level Python codeExpertise 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 productExperience and knowledge of Infrastructure as Code best practicesExperience in developing GenAI tools seen as a plusKnowledge of leading cross-function projects and R&D projectsKnowledge of agile project managementCompany : 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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