About the Role
We're seeking an experienced ML Engineer to join our Data Science team in Barcelona (Hybrid) to design and develop solutions for training and serving ML models, and Agentic applications. Become a part of our team and help us build the best AI platform possible.
Responsibilities
•Work with the Data Science team to design and develop Machine Learning and AI solutions
•Participate in the design and implementation of our internal AI platform
•Stay up to date with the latest developments in Machine Learning, Artificial Intelligence, and MLOps
•Provide internal users with training materials and communicate new developments
•Provide guidance and advice, ensure best practices are followed across the data science organization
Requirements
•Degree in a quantitative field (Computer Science, Engineering, Mathematics, Statistics, Physics, or other quantitative areas)
•2+ years of related experience as a Machine Learning or Software engineer
•Experience with Python, Java, C++ or any other object-oriented programming language
•Overall understanding of the process of creating machine learning models and their life cycle
•Knowledge of best practices to automate software development and ML operations: CI-CD, testing, and monitoring. Experience with Jenkins desirable
•Familiarity with Agentic application development, and understanding of the general concepts. Actively use AI as part of their day to day work
•Experience developing REST APIs and scalable systems
•Experience working in cloud platforms, distributed systems and Docker
•Familiarity with SQL databases
•Written and oral communication skills in English
Nice to Have
•Javascript and/or frontend experience is a plus
•Experience with Applied AI Tools: demonstrated comfort using practical AI tools such as Gemini, or other AI-powered assistants
•Experimentation Mindset: curiosity and eagerness to explore, experiment with, and integrate emerging AI-driven solutions into workflows
•AI-Enhanced Problem Solving: ability to effectively leverage AI tools to streamline processes, and enhance productivity
•Adaptability and Learning Agility: enthusiastic about continuously learning and quickly adapting to new AI features and capabilities
Conditions
•Prime Plus membership
•Competitive salary and benefits package, including flexible benefits, performance-based bonuses, birthday day off, discounts and partnerships
•Relocation support and premium equipment with role-based selection options and device ownership through equipment lifecycle program when it reaches its refresh cycle
•Free Coursera access, soft skills workshops, tech training, leadership development, and more
•Great onboarding program
•Personalised career paths and the eVOLVE Program to help discover, grow, and thrive
•Internal mobility opportunities for horizontal career changes and promotions
•Hybrid home-office model focused on outcome, not time-in-seat
•After-work events, padel tournaments, parties, and more; communities based on passions like sports and music
•No dress code, free fruit, coffee, and tea at offices
•Agile mindset environment with recognition at its core
