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Overview

Build and implement machine learning models for customers and advertisers to use.

What you do as Machine Learning Engineer Advertising

Our Advertising teams are home to ambitious product owners, data analysts/designers, software engineers and other data scientists, who all work together to maximize our advertising potential for customers and advertisers. You help deploy machine learning models such that they can deliver in the real-time, high-traffic context of Bol, where you employ your technical expertise to make the most out of these models, while adhering to business requirements. This role requires an experimental mindset – we can only build and deploy the best possible data science solutions based on tested and validated algorithms and implementation solutions.

You work with software engineers and data scientists from the Advertising teams to build solid bridges between data and personalized ads for customers. This is where your expertise makes all the difference. How can we take a new model into production? And how to facilitate refinement thereafter? We don’t think you’ll want to sit back and wait for ‘assignments’ here, because we eagerly encourage you to propose your own ideas for innovations. Innovations will be geared at, e.g.:

• Enhancing bol as an advertising platform for customers and advertisers
• Displaying the right ad in the right place at the right time
• Automating recommendations for advertisers that want to spend their time (and marketing budgets) more effectively
• Developing and supporting underlying software systems
• Identifying valuable new innovations, experiments, and advanced methods

Why you can make the difference

Because you’re a genius in conceptualizing, designing, developing and implementing machine learning models on CPU and GPU. You know the trade-offs and can make the right decisions at every layer of implementation based on model, hardware and latency/throughput requirements. You have extensive experience with Web Development (Kubernetes, Docker, API development), databases (PostgreSQL, BigTable, Redis or (nice to have) vector databases), and MLOps tooling such as MLFlow, Vertex AI, Kubeflow, and are excited about low-latency service development, with experience in (or eagerness to learn) Rust. On top of that, it would be nice if you also have experience in Go, Java, or C++. We embrace a hypotheses-driven approach and expect you to have a passion for experimentation. You are also eager to test and validate your models. We challenge you to propose several scenarios to solve any given problem. This is key to finding the (demonstrably!) best results. You also oversee the technical realization of your solutions into existing or new IT services, so collaborating with software engineers comes with the territory. Stakeholder management skills are a must, because you’ll work with colleagues from several domains and need to approach problems from a wide range of perspectives. It’s up to you to distill the optimal solution for a problem while maintaining effortless working relationships and open lines of communication with colleagues in the business and IT domains. And because our environment is in a constant state of flux, everyone needs to be eager learners. That goes for constantly developing skills as well as for exploring new terrain. You can always count on our community of experienced bol engineers for support.

Pros

• Your track record breathes dataYes, if you bring 5+ years of engineering experience to the table, preferably in ‘data-driven, personalized’ solutions and technical realizations
• You love lab settingsYes, if you love to experiment and innovate and can get colleagues on board for the ride
• You go from concept to realizationYes, if translating complex questions into the technical realization of scalable models and algorithms is totally your cup of Earl Gray

Cons

• You’re not into toolingNo, if FastAPI / Kubernetes / MLFlow is terra incognita
• You’re a soloistNo, if you’ve never worked with software engineers and don’t look forward to the experience
• You don’t deviate from the pathNo, if your natural inclination is to stay on the beaten path: it might be boring, but it feels ever so secure

This is where you’ll work

You’ll land in the Advertising tech fleet, one of our engineering departments that focuses on the different Advertising products. We develop innovations and technical tools to present advertisers with limitless opportunities to showcase their products/services on our platform. We zoom in on strategic topics, such as sponsored products and display advertising, as well as on audiences and the data we can make available to our advertisers.

You work with software engineers, data scientists from our Advertising teams and data analysts to build solid bridges between data and personalized ads for customers. Your machine learning models make all the difference

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