As an AI Machine Learning Engineer, you are a key technical contributor responsible for developing and deploying complex AI initiatives. You will focus on the end-to-end lifecycle of ML solutions, from technical design and coding to production deployment and continuous optimization. You will apply deep engineering rigor to build scalable, reliable systems that solve real-world R&D; challenges. you ensure they are integrated into robust software architectures that meet the highest standards of performance and reliability.Deliver high-quality code for data, modelling, and deployment pipelines, leading the team through engineering rigor.Agile Delivery: Work within an Agile framework to ensure research translates into predictable production value, meeting project milestones and deadlines.Business Advisory: Partner with technical and business stakeholders to translate business challenges into technical requirements and clear project updates.Who you areYou are passionate about AI and driven to deliver real-world impact through data.

You thrive in R&D-heavy; environments involving sparse or high-dimensional data, excelling at the intersection of experimental AI research and disciplined software engineering. You are a clear communicator who can explain technical trade-offs to both engineering peers and business stakeholders.Advanced AI/ML Engineering & Software CraftsmanshipProduction-Level Programming: Senior proficiency in Python, with a strong commitment to software engineering best practices (Design Patterns, Unit Testing, and Modular Code).



Solid understanding of modern AI/ML architectures and data platforms to build robust, performant systems.Data Engineering: Proficiency in handling data structures and pipelines to ensure model inputs are reliable and optimized.Advanced MLOps & Cloud InfrastructureAzure: Hands-on experience with the Azure ML SDK/CLI or Azure Databricks, including managed online endpoints, compute clusters, and data assets.CI/CD: Experience building and maintaining deployment pipelines using Azure DevOps or automation in Gitlab.Containerization: Proficiency in Docker for packaging and scaling AI/ML workloads within cloud-native environments.Ability to implement monitoring for system health (latency/CPU) and model performance (drift, accuracy, and data quality).

Experience working within an Agile/Scrum framework to deliver consistent project velocity.Project Delivery: Proven track record of taking ML models from a research phase to a stable production environment.Contextual PlusAcademic Background: Master's degree or higher in Computer Science, AI, Data Science, or a related field.Languages: Full professional proficiency in English; French is strongly preferred.What we offerA competitive compensation packageA yearly education budget to steep your learning curveA yearly sport budget because a fit body leads to a fit mindA adaptable working culture because your work-life balance matters to usA position that enables you to have an impact on 1'000s of people, and the whole company's growth.

📌 Machine Learning Engineer H/M (Barcelona)
🏢 Visium
📍 Barcelona