Strategic Machine Learning Leader for Advertising Optimization

1 dia atrás

Porto Alegre, Rio Grande do Sul, Brasil beBeeAdvertising Tempo inteiro US$140.000 - US$170.000

Job Title:

"Strategic Machine Learning Leader for Advertising Optimization"

Job Description

We are seeking a seasoned Strategic Machine Learning Leader to drive the development and implementation of cutting-edge advertising algorithms. As a key member of our team, you will design and deploy scalable machine learning systems that optimize revenue while enhancing user experience.

In this role, you will leverage your expertise in machine learning engineering, software development, and data analysis to build innovative solutions that drive business growth. Your knowledge of recommendation systems, advertising algorithms, NLP, and CV will be essential in driving ad performance and user engagement at scale.

Must-Have Skills:
  • 7+ years of experience in software development and machine learning engineering, including 3+ years focused on advertising systems.
  • Proven experience optimizing ad performance using both mature models and emerging ML technologies.
  • Expertise in one or more ML areas: Recommendation Systems, Advertising Algorithms, NLP, or CV.
  • Proficiency with Python, SQL, and modern ML frameworks (TensorFlow, PyTorch).
  • Familiarity with distributed data processing (Spark, Ray) and cloud infrastructure (AWS/GCP).
Key Outcomes:
  • Develop and scale advertising algorithms that optimize engagement and revenue simultaneously.
  • Apply cutting-edge ML approaches (e.g., reinforcement learning, deep learning for ranking) to improve ad performance.
  • Build scalable infrastructure to support real-time ad decisioning across millions of requests per day.
  • Conduct rigorous experiments (A/B and multivariate tests) to measure model impact on business KPIs.

Our ideal candidate is a passionate advocate for diversity, equity, and inclusion. We value a culture that celebrates individual differences and promotes equal opportunities for all.

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