Senior Engineering Manager, Ad Performance Recommendation (AI/ML)

Location: Flexible hybrid work model with 3 days per week in the Berlin office, Germany. Remote work abroad is available for up to 30 days.

Company

hirify.global is an AI-powered advertising technology company providing media, creative, and intelligence solutions for brands and advertisers.

What you will do

• Lead and grow the Ad Performance Recommendation team of Data Scientists, ML Engineers, and Software Engineers.
• Define technical direction and long-term strategy for ML and data science applications across the product suite.
• Drive the development, optimization, and scaling of ad technology ML models, including predictive and simulation techniques.
• Collaborate with cross-functional teams to deliver measurable customer and business impact.
• Ensure privacy, security, and ethical AI compliance in production ML applications.
• Mentor engineers and data scientists, remove delivery obstacles, support recruiting, and shape AI platform architecture.

Requirements

• 7+ years of experience building services and products.
• 5+ years of experience applying machine learning to real-world problems and 3+ years leading teams.
• Hands-on experience with Python, SQL, PyTorch, TensorFlow, and scalable ML systems in production.
• Experience mentoring, coaching, conducting code reviews, and using pair programming with data scientists and ML engineers.
• Understanding of security, privacy, and compliance requirements for systems using personal data.
• M.Sc. or Ph.D. in mathematics, computer science, AI, physics, or a related field; excellent written and spoken English required.

Culture & Benefits

• Ownership culture with autonomy and the opportunity to influence products.
• Collaboration with major advertising platforms and online marketers.
• Mentorship, training, and professional development resources.
• Healthcare packages, mental health services, and support for work-life balance.
• Equity options, performance-based grants, and flexible hybrid work arrangements.

Hiring process

• Recruiter meeting followed by a meeting with the team manager.
• Subject matter interviews including a case study and domain discussion.
• Final leadership meeting with the Chief Technical Officer.