Senior Machine Learning Engineer

Senior Machine Learning Engineer

Development Amsterdam

This is

At , we're engineered for ambition. We empower our teams with the culture and support they need to own their careers. The people of are motivated problem-solvers who tackle unique technical challenges at scale, delivering innovative and ethical solutions to help the world's best businesses achieve their ambitions faster, and we're looking for a motivated Machine Learning Engineer to join our team in Amsterdam.

Senior Machine Learning Engineer

is looking for a Senior Machine Learning Engineer to join our team in Amsterdam, a person sitting at the cornerstone of algorithms, mathematics, and engineering, who can solve problems by designing and implementing production-ready machine learning solutions. You will be responsible for building, developing and deploying algorithms that power data products at .

In this role, you will:

• Research, design, implement, train, deploy and monitor machine learning algorithms, either for batch prediction or real-time. Examples are:on-line learning algorithms to pick the best optimization decision in a changing environment, clustering algorithms to group customers/shoppers, supervised and semi-supervised learning methods for inference on risk patterns or graph analysis, representation learning for behavior prediction and monitoring, Anti-Money Laundering (AML) systems and real-time anomaly detection based on time-series modeling;
• Develop orchestrated pipelines for analytical purposes and machine learning training;
• Contribute to ongoing automation efforts for our experiments, training runs, validation runs and monitoring before, during and after deployment. Furthermore, collaborate with MLOps to improve our machine learning tooling;
• Create and iterate on state of the art machine learning algorithms with both merchant and product audiences;
• Stay up-to-date with the latest research and developments in the machine learning field, and apply this where applicable.

Who You Are:

• You have 8+ years of experience as a machine learning or data scientist;
• You have experience with the full machine learning model lifecycle in production flows;
• You have experience with building and deploying Deep Learning models;
• You have experience leveraging a big data framework to create the pipelines needed to feed the models with appropriate data;
• You have a good understanding of software engineering practices as well as data engineering and MLOps principles;
• You have knowledge of data science and statistics and machine learning techniques. These include a strong grounding in statistical inference, machine learning for prediction, and causal inference. Experience with Deep Learning is a must have.;;
• You have strong familiarity with the standard data science toolkit, such as (py)spark, (Trino) SQL, Tensorflow, PyTorch, XGBoost/LightGBM, Pandas, MLFlow or similar MLOps frameworks, and Airflow;
• You have an experimental mindset with a launch fast and iterate mentality. Extensive experience with designing and running experiments is essential;
• You proactively take the lead in projects, from ideation to deployment. You have experience working with a wide range of stakeholders and can clearly communicate complex outcomes over a wide range of audiences.

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