Senior Machine Learning Engineer (f/m/d)

About the role

This role focuses on architecting and deploying recommendation systems that handle large user bases and billions of daily requests. The work involves identifying signals from large datasets, developing relevance models and bidding strategies, and directly impacting company revenue through advanced machine learning techniques. Success means delivering scalable, high-throughput, and low-latency systems.

The Senior Machine Learning Engineer will own the full lifecycle of production models, including monitoring, performance analysis, and iterative improvements. This requires a data-driven approach to enhance model effectiveness. Collaboration with backend engineering teams is essential to ensure seamless integration and industrialization of machine learning solutions, making models reusable and robust.

A key aspect of the role is conducting rigorous A/B testing and experimentation. The engineer will validate hypotheses and measure the impact of new features on business metrics. This involves a continuous cycle of development, testing, and refinement to optimize recommendation systems within the adtech environment.

The salary for this position ranges from $90,000 to $135,000 annually.

Skills that matter here

• machine learning: This role requires applying machine learning techniques to develop and refine recommendation systems and bidding strategies.
• deep learning: Expertise in deep learning is necessary for building and optimizing neural network architectures for recommendation tasks.
• TensorFlow: Hands-on experience with TensorFlow is expected for developing and optimizing deep learning models.
• PyTorch: The role involves using PyTorch for building and optimizing neural network architectures.
• data engineering: An understanding of data engineering principles is beneficial for handling large-scale datasets and integrating ML solutions.
• Spark: Experience with Spark is valuable for working with large-scale distributed data processing systems.

Who this role suits

• You have a background in developing and deploying production-grade recommendation systems in high-volume environments.
• You possess demonstrated expertise in deep learning, specifically in building and optimizing neural networks.
• You consider yourself a software engineer at heart, capable of building robust and scalable solutions.
• You are adept at rigorous A/B testing and experimentation to validate hypotheses and measure impact.

From the employer

What You Will Do

• Architect and deploy a high-throughput, low-latency recommendation system capable of scaling to millions of users and billions of daily requests.
• Leverage Large Scale Dataset: identify relevant signals to improve model performance.
• Develop and refine relevance models, bidding strategies, using advanced machine learning techniques, directly influencing the company revenue.
• Own the end2end lifecycle of production machine learning models, including rigorous monitoring, in-depth performance analysis, and data-driven iterative improvements.
• Collaborate closely with backend engineering teams to design and implement robust, scalable, and production-ready machine learning solutions, ensuring seamless integration and industrialization of reusable models and assets.
• Conduct rigorous A/B testing and experimentation, Validate your hypothesis and measure the impact of new features on key business metrics.

Who You Are

• You have 5+ years of proven experience developing and deploying production-grade recommendation systems in a high-volume environment (e.g., adtech, e-commerce, search).
• You demonstrated expertise in deep learning, with hands-on experience building and optimizing neural network architectures for recommendation tasks using TensorFlow, PyTorch or Jax.
• You are a software engineer at heart.
• Plus: you have understanding of data engineering principles.
• Plus: experience working with large-scale distributed data processing systems (e.g., Spark, Flink, Kafka) and data storage solutions (e.g., AWS Athena, S3, MySQL).

Benefits to Support Your Ambitions

• Regular feedback and our development program support your growth, helping you expand your skill set and achieve your career goals.
• From signing to settling in Hamburg, we’ve got you covered. Need a visa? No problem. Ready to build your new life and career at adjoe in Hamburg? We support every ambition—from learning German to a relocation bonus that helps you settle in and make Hamburg feel like home.
• We work in a hybrid setup with 3 core office days, plus flexible working hours. Enjoy 30 vacation days, 3 weeks of remote work per year, and free access to an in-house gym with lots of different fitness classes and mental health support through our Employee Assistance Program (EAP).
• Enjoy the Alster lake view from our central office with top-notch equipment, fun open spaces, and a large variety of snacks and drinks.
• Participate in regular team and company events, including hackathons and social gatherings. We work together, and we celebrate together, too.