Machine Learning Engineer
The following information aims to provide potential candidates with a better understanding of the requirements for this role.Role OverviewMachine Learning Engineers play a pivotal role in bringing AI solutions from concept to production. They champion best practices in industrial-grade ML development and ensure that machine learning solutions are designed with scalability, reliability, and maintainability in mind.By building production-ready ML pipelines or embedding existing models into enterprise-grade ecosystems, ML Engineers help bridge the gap between experimental data science and operational IT environments. Their work spans the full lifecycle of AI services—from development and deployment to monitoring and continuous improvement.They act as a key interface between AI & Analytics teams and IT Production, ensuring that deployed models are supported by robust data pipelines, automation, and performance monitoring aligned with both technical and business needs.Key ResponsibilitiesAs part of Machine Learning initiatives, ML Engineers will:Collaborate closely with Data Scientists to design and implement solutions that account for production constraints from the outset, including infrastructure selection, deployment architecture, and serving mechanisms (e.g. batch vs. real-time processing, API design, data ingestion patterns).Contribute to the automation and industrialization of ML pipelines to support seamless integration and deployment into production environments (e.g. containerization, test automation, CI/CD implementation).Assist Data Scientists in leveraging standard enterprise platforms and tools to build, deploy, and monitor AI services effectively.Work alongside IT Production teams to configure and optimize target environments for AI workloads.Ensure models are stable and performant in production, retrained when necessary (manually or automatically), and monitored from both operational and business perspectives.Experience & Technical SkillsRequired ExperienceMinimum 4 years of relevant experience in Machine Learning engineering or similar rolesMandatory Technical SkillsContainerization and virtualization technologiesAI platforms and development environmentsCI/CD pipelines (e.g. GitLab CI)Versioning of code, data, and modelsAdvanced proficiency in PythonDependency and package management toolsRelational databases (PostgreSQL)Preferred Technical SkillsExperience with system integrations across heterogeneous environments (distributed systems, mainframe, etc.)Model optimization and compression techniquesxjsrcvq ELT / ETL frameworksBig data ecosystems (e.g. Spark)Stream and data flow processing toolsData visualization solutionsBusiness KnowledgeSolid understanding of Agile methodologiesSoft Skills & CompetenciesStrong written and verbal communication skillsHighly results-driven with a strong sense of ownershipDetail-oriented and methodicalCreative problem solver with an innovative mindsetActively invests in continuous learning and skill developmentDemonstrates efficiency and effectiveness in deliveryChallenges conventional approaches and explores new ways of workingDisplays energy, accountability, and commitment to achieving impactful outcomesOpen-minded and constructive when engaging with change, feedback, and diverse perspectives