Machine Learning Ops Engineer

Description ContextWould you like to work in a dynamic, international, technological environment, helping build something great from the ground up?Following the Admiral Group Business Strategy, Admiral EU has launched an ambitious Data & Analytics (D&A) initiative to build strong foundations in terms of skills, governance and technology. In many areas of our business, data is essential to better understand the challenges that we face to make sound strategic and operational decisions.We have been delivering business value from Big Data and Machine Learning for a few years, and we now seek to industrialize and automate the whole D&A value chain. Now, We want to minimise the time it takes to deploy our models so we can extract value faster and we would like to onboard skilled and motivated candidates like you!Role DescriptionWe are looking for a technical expert with a proven track record Machine Learning Operations. You will lead on the development and implementation of technical MLOps best practices and influence an international cohort of data scientists towards adoptionAt a relational level, you will maintain direct interaction with the Advanced Analytics team to influence the modeling process from start to finish, as well as with the Data Development Engineers team to optimize flows.What do we offer?Great opportunities for growth and professional developmentAlthough our offices are on #Sevilla, we have a #RemoteFirst policy, adapting your day to your needsFlexible working hours, with 25 days of working vacation per year Participation in the company's share system ...and many other things that make us the 2nd best company to work for in Spain in 2023, according to Great Place To Work Spain! Requirements This is you!Essential requirements:Mid-senior professional with at least 4 years experience in a similar roleCloud Computing: in-depth expertise of AWS SagemakerMachine Learning: hands-on development of end-to-end data science workflowsDevOps: proven experience in CI/CD, automated testing and software engineering principlesInfrastructure as code: proficient in tools like Terraform, CDK or equivalent to provision resourcesMonitoring: familiar with best practice on logging, monitoring and observabilityExperience to influence Data scientists to adopt the ML OPS framework Fluency in working EnglishResidence in SpainDesirable requirements:Vendor relationship managementExperience mentoring junior team membersAble to communicate complex concepts to a wide range of non-technical stakeholders Location (Hybrid)