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Sobre esta vaga de Senior Machine Learning Engineer na WPP

WPP · Híbrido · Copenhagen

WPP is the trusted growth partner for the world’s leading brands. 

We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. 
 
We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise.
 
Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. 
 
For more information, visit WPP.com.
 

 

Location Requirement

This is a hybrid role based in Copenhagen, Denmark. Candidates must currently reside in Denmark or be willing to relocate independently, as relocation support is not provided for this position.

 

About Open Intelligence 

We are the Activation arm of WPP Open Intelligence. Open Intelligence is a highly strategic initiative at the intersection of data science, advertising technology, and audience insights. Our team is building the data and ML systems that power the next generation of marketing and media intelligence, deeply integrated and adopted by the largest supply-side partners in the AdTech industry. With operations spanning the US, UK, and ongoing expansion into EMEA and APAC, our system continuously interacts with up to 98% of the population in our active markets. 

Based in our Copenhagen office, you will join a broader Open Intelligence team of roughly 50 people, including 14+ data scientists and a strong group of engineers working across data and ML production systems. 

 

Who We Are Looking For 

We are looking for a Senior ML Infrastructure Engineer with a strong background in infrastructure, platform engineering, data systems, or large-scale software engineering. 

You do not need to come from a pure ML infrastructure background to succeed in this role. What matters most is that you have strong engineering fundamentals and experience building robust, scalable, production-grade systems. You may have built cloud platforms, backend services, distributed data pipelines, or internal developer tooling, and you are excited to apply that experience to systems that support modern AI and ML workloads. 

You are comfortable working close to both engineers and data scientists, translating experimental or research-oriented work into reliable, maintainable production components. You care about system design, operational excellence, automation, observability, and maintainability. You value clean interfaces, strong testing practices, and infrastructure that can scale with growing demands. 

Beyond your technical skills, you are a strong communicator who can collaborate across disciplines, explain trade-offs clearly, and contribute to a high-trust, high-output team environment.

 

Why we're hiring:

We are hiring because we need experienced engineers who can help us design for scale, improve platform reliability, reduce operational friction, and build the foundations that allow advanced AI work to deliver real-world impact. To support this product evolution, our infrastructure is undergoing massive global expansion. By the end of this year, we will be fully operational across the rest of the EMEA and APAC regions. Concurrently, we are deepening our integrations to support even more of the largest supply-side partners in the AdTech industry. 

 

What you'll be doing:

  • Design, build, and maintain scalable, production-grade infrastructure that supports data and ML workloads in the cloud, primarily on GCP. 
  • Collaborate closely with data scientists and engineering peers to translate research prototypes into robust, production-ready systems. 
  • Design and implement data and ML platforms with strong reliability, scalability, observability, and operational maturity. 
  • Identify and address technical debt, bottlenecks, and inefficiencies across infrastructure and platform components. 
  • Contribute to engineering best practices across CI/CD, version control, testing, automation, and repo maintenance. 
  • Participate in knowledge sharing, technical discussions, and continuous improvement across the team. 

 

What You Will Need 

  • 4+ years of experience in infrastructure engineering, platform engineering, data engineering, or large-scale software engineering. 
  • Strong practical experience with Python and SQL. 
  • Experience designing and operating systems in cloud environments such as GCP, AWS, or Azure. 
  • Familiarity with ML frameworks such as PyTorch or TensorFlow. 
  • Familiarity with MLOps tools such as MLflow, Kubeflow, or similar ML platforms. 
  • Experience with CI/CD, version control, API design, and testing best practices. 
  • Experience with building or supporting large-scale data or ML platforms, cloud platforms or other scalable production systems. 
  • A strong interest in building reliable, automated, and well-engineered platforms that support advanced AI and data workloads. 
  • A collaborative mindset and a willingness to work across disciplines in a fast-moving engineering environment.

 

Nice to Have 

  • Familiarity with data processing and orchestration tools such as Spark, Flink, Airflow. 
  • Experience with infrastructure and deployment tooling such as Docker, ideally Kubernetes. 
  • Experience with strongly typed languages such as Java, Go, or C++. 
  • Interest in using AI coding assistants to improve engineering productivity. 

 

Who you are:

You're open: We are inclusive and collaborative; we encourage the free exchange of ideas; we respect and celebrate diverse views. We are open-minded: to new ideas, new partnerships, new ways of working.

You're optimistic: We believe in the power of creativity, technology and talent to create brighter futures or our people, our clients and our communities. We approach all that we do with conviction: to try the new and to seek the unexpected.

You're extraordinary: we are stronger together: through collaboration we achieve the amazing. We are creative leaders and pioneers of our industry; we provide extraordinary every day.

 

What we'll give you:

Passionate, inspired people – We aim to create a culture in which people can do extraordinary work.

Scale and opportunity – We offer the opportunity to create, influence and complete projects at a scale that is unparalleled in the industry.

Challenging and stimulating work – Unique work and the opportunity to join a group of creative problem solvers. Are you up for the challenge?

#LI-Hybrid 

We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process.

WPP is an equal opportunity employer and considers applicants for all positions without discrimination or regard to particular characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

Please read our Privacy Notice (https://www.wpp.com/en/careers/wpp-privacy-policy-for-recruitment) for more information on how we process the information you provide.

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Sobre a WPP

At WPP, we believe in the power of collaboration and the impact of bold ideas. We champion creativity, providing a dynamic environment where you can contribute to groundbreaking work, develop your skills, and become part of a global community of passionate individuals. Explore a world of opportunities at WPP and discover a career that fuels your passion and empowers you to make a difference.


We use AI tools in our hiring process to enhance efficiency and improve the candidate experience, such as helping match candidates to roles or assist with scheduling. These tools support, but never replace, human decision-making. All final hiring decisions are made by people. We are committed to using AI ethically, ensuring fairness, minimizing bias, and protecting candidate data in line with privacy regulations. If you have questions about how AI is used in our recruitment process, please reach out to [email protected]. 

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