AI Machine Learning Engineer

About the role

Title: AI Machine Learning Engineer Client: Chemical Industry Location: Barcelona About us At Visium, we partner with leading enterprises to define their AI & Data strategy, execute large-scale transformations, and integrate AI across operations, securing their organization's future. Leveraging our expertise in strategy, cloud platform engineering, and artificial intelligence, we empower our clients to unlock and scale the power of their data. We are currently spearheading a major transformation for a client in the Flavor and Fragrance sector and are seeking exceptional talent to contribute to this impactful work. This is a unique opportunity to join our client's team (as a direct employee of the client). You will shape the future of the organization, collaborating with senior leaders and cutting-edge technologies to deliver AI-driven innovation and tangible business impact. Role As a 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 R&D 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. Responsibilities Technical Implementation: Contribute to the design and development of scalable, maintainable AI solutions aligned with modern best practices. Hands-on Development: Deliver high-quality code for data, modelling, and deployment pipelines, leading the team through engineering rigor. MLOps Mastery: Implement and maintain robust MLOps workflows, focusing on automated CI/CD, containerization, and model observability. 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 are You 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 Craftsmanship Production-Level Programming: Senior proficiency in Python, with a strong commitment to software engineering best practices (Design Patterns, Unit Testing, and Modular Code). System Design: Solid understanding of modern AI/ML architectures and data platforms to build robust, performant systems. Modeling Depth: Deep knowledge of AI/ML algorithms and the mathematical foundations required to tune models for high-precision R&D use cases. Data Engineering: Proficiency in handling data structures and pipelines to ensure model inputs are reliable and optimized. Advanced MLOps & Cloud Infrastructure Azure: 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. Observability & Reliability: Ability to implement monitoring for system health (latency/CPU) and model performance (drift, accuracy, and data quality). Professional Collaboration Agile Methodology: Experience working within an Agile/Scrum framework to deliver consistent project velocity. Technical Translation: Ability to communicate complex trade-offs clearly to non-technical stakeholders. Project Delivery: Proven track record of taking ML models from a research phase to a stable production environment. Contextual Plus Academic Background: Master's degree or higher in Computer Science, AI, Data Science, or a related field. Domain Expertise (Preferred): Exposure to formulation, chemistry or the Fragrance & Flavour industry. Languages: Full professional proficiency in English; French is strongly preferred.

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