Senior Machine Learning Engineer, Intent HQ

• 7+ years of industry experience writing clean, production-grade code, with a deep focus on data engineering, machine learning and MLOps workflows
• Expertise in distributed data processing frameworks such as Spark, handling multi-terabyte datasets to generate valuable insights
• Proficiency in building and orchestrating data and machine learning pipelines, supporting data engineering, model training, and inference at scale
• Python as the primary programming language
• Experience designing and maintaining large-scale, data-intensive applications that can support real-time or near-real-time workloads
• Proven experience with CI/CD pipelines for packaging, deploying, and operating AI models at scale
• Hands-on experience with MLOps infrastructure design and implementation, ensuring smooth operations of models in production environments
• Ability to take initiative and ownership of tasks, with excellent collaboration and communication skills
• Experience working with at least one of the major cloud providers (AWS, GCP, Azure)

Desirable

• We are looking for a Barcelona based Senior Machine Learning Engineer who is passionate about leveraging data, scaling ML systems, and building robust MLOps pipelines to deliver AI solutions at scale
• We are looking for a Senior Machine Learning Engineer who is passionate about leveraging data, scaling ML systems, and building robust MLOps pipelines to deliver AI solutions at scale. You will collaborate with data scientists, product teams, and engineers to design and maintain the infrastructure that powers our AI products, with privacy, security, and data ethics as core principles
• Design, implement, and manage our end-to-end Data & ML Platform, which supports all AI product development and deployment. This includes developing and improving data pipelines, feature engineering for downstream models, and orchestration of complex data workflows
• Productionise machine learning models and manage them across the full lifecycle—from model training to deployment and monitoring—while ensuring scalability, security, and performance
• Advise on architectural patterns and tooling to enable data and machine learning workloads at scale. You’ll work closely with data scientists to ensure the platform supports experimentation, model training, and inference efficiently
• Collaborate with product and consulting teams to design and deliver platform capabilities that directly benefit our customers
• Champion a culture of experimentation and continuous improvement by taking ownership, learning from mistakes, and contributing to the growth of your colleagues