This is a remote position.
Are you motivated by working on machine learning applied to real-world products, with a direct impact on the business and in a high-scale technological environment?
This opportunity is with an international AdTech company specializing in programmatic advertising and the development of its own platform to optimize digital campaigns through data, recommendation models, and performance analysis.
As a Senior Machine Learning Engineer, you’ll work on developing, maintaining, and optimizing the recommendation engine that helps determine which ad creatives perform best based on the client, campaign, audience, and context. This will be a hands-on role involving data analysis, model development, and close collaboration with the creative team.
Responsibilities
Develop, maintain, and optimize machine learning models applied to recommendation systems and the selection of ad creatives.
Work on the recommendation engine to identify which ads perform best based on client, campaign, audience, and context.
Analyze performance data to detect patterns, opportunities for improvement, and new modeling hypotheses.
Propose, validate, and implement new approaches that improve decision-making within the platform.
Participate in the full model lifecycle: analysis, feature engineering, training, deployment, monitoring, and maintenance.
Collaborate with the creative team to understand their needs and translate them into data-driven technical solutions.
Work alongside the Machine Learning, MLOps, and technology teams to bring models into production in a robust, scalable, and maintainable manner.
Profile Requirements
5+ years of experience in Machine Learning, applied Data Science, or Machine Learning Engineering roles.
Solid knowledge of machine learning and deep learning algorithms.
Proficiency in Python, SQL, statistics, and ML frameworks/libraries.
Experience with or strong interest in recommender systems, ranking, personalization, or optimization.
Ability to work with large volumes of data and solve complex challenges.
Analytical, proactive, and product-oriented mindset.
Strong communication and teamwork skills, and the ability to adapt to a constantly changing environment.
Fluent English.
The following will be highly valued
Previous experience in AdTech, programmatic advertising, DSPs, or real-time bidding.
Experience in sectors such as gaming, marketplaces, e-commerce, fintech, or large-scale digital products.
Knowledge of Java, Scala, or technologies related to distributed systems.
Experience in ML system design, architecture, or the technical design of machine learning solutions.
Experience working with MLOps teams or participating in model deployment and maintenance.
Benefits
Remote work model from anywhere in Europe (with quarterly visits to Barcelona).
Flexible hours and a focus on work-life balance.
Meal vouchers and private health insurance starting on your first day.
LinkedIn Learning and AWS/Cloud Guru certifications paid for by the company.
Gym membership included.
Annual salary review tied to your performance.
23 days of vacation + 1 extra day in December.
2 weeks/year of “work from anywhere” outside your usual location.
Annual team-building events and team-building activities.
High-caliber international projects and real visibility for your achievements.
Startup atmosphere: dynamic, collaborative, flexible, with room to grow and contribute your own ideas.
Continuous learning with access to cutting-edge technologies and methodologies.
Be part of the fastest-growing phase of a leading tech company.
Ready to make your mark in the world of Machine Learning? If you’re looking to take the next big step, we want to surprise you. Take the plunge and apply now.
iTalenters is an international AdTech company specializing in programmatic advertising and the development of its own platform designed to optimize digital campaigns through data, recommendation models, and performance analysis. The company focuses on building machine learning-driven solutions that determine which ad creatives perform best based on client, campaign, audience, and context. Their platform leverages advanced data science and recommendation engines to help clients make data-driven decisions in real-time bidding and digital advertising.
