Top Machine Learning Jobs in Barcelona

The Product Manager will lead the strategy for matching algorithms, oversee their lifecycle, and collaborate with various teams to meet market needs.

Lead the AI product strategy at Goodnotes, overseeing development across various AI initiatives and ensuring alignment with company vision.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

As a Commercial Data Analyst at Superbet, you will analyze customer behavior and product performance, framing questions and delivering insights to influence strategy across teams.

Lead multi-stream client programs as the primary contact, ensuring outstanding delivery and strategic alignment with business goals. Manage Engagement Managers, drive account growth, and build strong relationships with senior stakeholders.

The Data Scientist will develop ML models for image recognition, work on product categorization, and collaborate with engineers to deploy scalable solutions.

The Senior Product Manager will lead product initiatives, develop roadmaps, collaborate with cross-functional teams, and drive product lifecycle from ideation to launch, ensuring alignment with business goals.

The Refining and Petrochemical Process Optimization Engineer analyzes process data, works on AI-driven optimization models, and collaborates with clients to improve operations and drive efficiency.

The Product Manager will lead the Market Intelligence team to translate digital asset data into actionable insights, drive product strategy, conduct market studies, and enhance Keyrock's services based on data-driven recommendations.

The Senior Machine Learning Engineer will develop ML tools for the LiveOps Automation team, improving player experiences and guiding less experienced members.

The Senior AI Engineer will design and develop production-grade AI services and APIs, drive the development lifecycle, mentor team members, and resolve technical challenges.

As a Data Scientist, you will design, train, and validate machine learning models, collaborate with professionals, and ensure transparency and reproducibility of results.

As a Machine Learning Senior Engineer, you will develop algorithms, enhance pipelines, analyze data, and mentor team members while solving unique modeling challenges.

As a Machine Learning Engineer, you will develop and improve algorithms, implement scalable solutions, and analyze data to provide business insights.

As a Lead Machine Learning Engineer, you will oversee complex projects, mentor teams, drive ML practices, and shape technical strategy.

The Data Scientist/ML Engineer will analyze data, develop data science solutions, and collaborate with teams to enhance ad effectiveness while optimizing machine learning models.

Responsible for the end-to-end lifecycle of ML solutions focusing on API development and full-stack engineering, utilizing advanced ML libraries and LLMs.

As an Applied Machine Learning Engineer, you'll apply advanced analytics and machine learning techniques to optimize rewards programs and develop new initiatives, working in a multidisciplinary team and impacting millions of users.

The Machine Learning Engineer will design, build, and maintain scalable ML systems, optimize ML pipelines, implement MLOps, and collaborate with teams to deploy models into real-time products.

The Senior Infrastructure Engineer will deploy, scale, and maintain services for the ML/AI team, collaborating closely with ML Engineers and Data Scientists.

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.

The role involves designing experiments, improving ML processing, writing Python code, and collaborating on automation solutions for task similarity.

The Machine Learning Specialist will develop production systems using LLMs, integrate backend services with Python, and design data pipelines. They will also analyze user behavior and may apply computer vision techniques.

Lead a team of Data Scientists and Analysts to develop strategies, frameworks, and infrastructure for actionable insights and predictive modeling. Partner with various teams to drive player engagement and business performance through analytics and ML solutions.

The Head of Data Product will oversee the development of data products, defining strategy, leading cross-functional teams, ensuring quality, and establishing metrics for success.