Principal ML Engineer | AI AdTech | 50 Million Users | Berlin (Hybrid)

AI Futures have been exclusively retained to appoint a Principal Machine Learning Engineer for one of the fastest growing Companies in Europe who have seen so much success since inception, they have not required a single penny of external investment. Their revolutionary flagship platform engages over 50 million users which is driving unparalleled returns for their customers.

This is a rare opportunity to join a very profitable, scaling business who are investing heavily in data infrastructure, analytics, and AI to power its next phase of growth.

In this role, you will spearhead the creation of transformative ML models to enhance its industry-leading platform. Through close collaboration with the Berlin-based technology leadership team, you’ll define and implement a high-impact ML strategy, developing cutting-edge recommendation systems and optimising user lifetime value in a dynamic, data-driven environment.

Ultimately, your contributions will shape the future of AdTech!

Hybrid: 2 days per week onsite in Berlin.

The fixed salary is up to €120k.

The role:

• Design, develop, and deploy advanced ML models, such as recommendation systems and causal ML solutions, to optimize user acquisition and engagement on Almedia’s platform.
• Formulate strategies to maximize player lifetime value (pLTV) using sequence modeling and Bayesian techniques, adapting to evolving player behaviors and market conditions.
• Collaborate with product, engineering, and growth teams to align ML solutions with Almedia’s business objectives, enhancing ROAS and retention metrics.
• Conduct thorough statistical analyses, including A/B testing and regression, to validate model performance and support data-driven decision-making.
• Oversee the end-to-end ML pipeline, identifying high-value opportunities, building scalable solutions, and optimizing models to improve Almedia’s ad campaign effectiveness.

The Candidate:

• Advanced ML Proficiency: 5+ years expertise in Python, SQL, and cloud platforms, with a proven track record of building and deploying ML models for AdTech challenges like pLTV optimization.
• Statistical Expertise: Comprehensive knowledge of statistical methods, including A/B testing, probability, and regression, to ensure robust ML solutions.
• Cross-Functional Collaboration: Strong ability to work with diverse teams, translating complex ML insights into actionable strategies for non-technical stakeholders.
• Analytical Problem-Solving: Sharp analytical skills to address intricate AdTech challenges, such as reward system optimization, with a focus on measurable business impact.

AI Futures Ltd | Filling the AI Skills Gap ®