3 дня назад
Senior/Staff ML Scientist – Bidding & Optimization (f/m/d)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior/Staff ML Scientist – Bidding & Optimization (AdTech): Building machine-learning systems for real-time bidding, budget pacing, auctions, and allocation across mobile advertising products with an accent on reinforcement learning, objective-based optimization, and control theory. Focus on translating research into sub-millisecond production systems, designing scalable Bayesian inference and data pipelines, and optimizing high-throughput algorithms serving tens of thousands of requests per second.
Location: Applications welcome worldwide; relocation support is provided to Hamburg, Germany.
Company
builds mobile advertising technologies for user acquisition, rewarded engagement, programmatic in-app advertising, and monetization.
What you will do
- Build foundational algorithms for real-time bidding, budget pacing, auction mechanics, and allocation.
- Translate academic research into robust production code optimized for sub-millisecond latency.
- Develop reinforcement learning, objective-based optimization, and control-theory systems for bidding, pricing, and budget pacing.
- Architect scalable Bayesian inference systems and data pipelines for sparse, high-dimensional advertising data.
- Deploy algorithmic frameworks serving millions of requests and evaluating tens of thousands of requests per second.
- Lead architectural discussions, collaborate with Product Managers and Engineers, mentor junior scientists, and guide research direction.
Requirements
- PhD in Computer Science, Statistics, Mathematics, or Physics, or an MSc with extensive industry research experience.
- At least 4 years of experience optimizing complex systems through automated algorithms in AdTech, marketplaces, or high-frequency trading.
- Peer-reviewed publications or equivalent research depth in computational advertising, auction theory, mechanism design, or game theory.
- Deep practical and theoretical expertise in reinforcement learning, objective-based optimization, control theory, bidding, pricing strategy, or budget pacing.
- Strong proficiency in Python and experience handling large-scale, sparse, high-dimensional data.
- Ability to design production systems for high-throughput, low-latency environments.
Culture & Benefits
- Work on infrastructure affecting 770 million users and billions of decisions every day.
- Operate within a diverse, global team representing more than 40 countries.
- Collaborate directly across research, product, and engineering functions.
- Relocation support to Hamburg, Germany is available.
- Work on high-impact adtech systems with frequent production delivery and rapid feedback cycles.
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