ph3Title /h3 ul liAI Machine Learning Engineer /li liLocation: Barcelona /li /ul h3Role /h3 pAs an AI/ML 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. This is a high‑impact technical role. You will apply deep engineering rigor to build scalable, reliable systems that solve real‑world RD challenges. You don't just build models; you ensure they are integrated into robust software architectures that meet the highest standards of performance and reliability. /p h3Responsibilities /h3 ul liTechnical Implementation: Contribute to the design and development of scalable, maintainable AI solutions aligned with modern best practices. /li liHands‑on Development: Deliver high‑quality code for data, modelling, and deployment pipelines, leading the team through engineering rigor. /li liMLOps Mastery: Implement and maintain robust MLOps workflows, focusing on automated CI/CD, containerization, and model observability. /li liAgile Delivery: Work within an Agile framework to ensure research translates into predictable production value, meeting project milestones and deadlines. /li liBusiness Advisory: Partner with technical and business stakeholders to translate business challenges into technical requirements and clear project updates. /li /ul h3Who you are /h3 pYou are passionate about AI and driven to deliver real‑world impact through data. You thrive in RD‑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.



/p h3Requirements /h3 h3Advanced AI/ML Engineering Software Craftsmanship /h3 ul liProduction‑Level Programming: Senior proficiency in Python, with a strong commitment to software engineering best practices (Design Patterns, Unit Testing, and Modular Code). /li liSystem Design: Solid understanding of modern AI/ML architectures and data platforms to build robust, performant systems. /li liModeling Depth: Deep knowledge of AI/ML algorithms and the mathematical foundations required to tune models for high‑precision RD use cases. /li liData Engineering: Proficiency in handling data structures and pipelines to ensure model inputs are reliable and optimised. /li /ul h3Advanced MLOps Cloud Infrastructure /h3 ul liAzure: Hands‑on experience with the Azure ML SDK/CLI or Azure Databricks, including managed online endpoints, compute clusters, and data assets. /li liCI/CD: Experience building and maintaining deployment pipelines using Azure DevOps or automation in Gitlab. /li liContainerization: Proficiency in Docker for packaging and scaling AI/ML workloads within cloud‑native environments. /li liObservability Reliability: Ability to implement monitoring for system health (latency/CPU) and model performance (drift, accuracy, and data quality). /li /ul h3Professional Collaboration /h3 ul liAgile Methodology: Experience working within an Agile/Scrum framework to deliver consistent project velocity. /li liTechnical Translation: Ability to communicate complex trade‑offs clearly to non‑technical stakeholders. /li liProject Delivery: Proven track record of taking ML models from a research phase to a stable production environment. /li /ul h3Contextual Plus /h3 ul liAcademic Background: Master’s degree or higher in Computer Science, AI, Data Science, or a related field. /li liDomain Expertise (Preferred): Exposure to formulation, chemistry or the Fragrance Flavour industry. /li liLanguages: Full professional proficiency in English; French is strongly preferred. /li /ul /p #J-18808-Ljbffr

📌 AI Machine Learning Engineer (Barcelona)
🏢 Visium
📍 Barcelona