Senior Machine Learning Engineer, Benefits Personalization

S'more about the team

The position is part of the Growth Alliance, which has the mission to empower the HelloFresh business to convince more customers to try, recommend, or return to our products. Within Growth, the Customer Value Optimization Tribe maximizes long-term customer value by optimizing pricing, personalizing benefits, forecasting customer value (CLV), and creating compelling incentives that drive retention and revenue growth. As a Senior ML Engineer within our Benefits Personalization Squad , you will own the data infrastructure that powers personalized customer experiences at HelloFresh: helping us deliver the right benefits, incentives, and offers to the right customers at the right time.

Our Engineers assume development and operational responsibility for the HelloFresh Platform that enables serving millions of customers globally by providing the best & efficient experience for our customers and internal users.

Above all, we are looking for people who will make HelloFresh better. We believe there are many different ways of developing skills and we love diverse experiences! So even if you don’t “tick all the boxes” but think you’d thrive in this role, we would really like to learn more about you.

Lettuce share what this role will be responsible for

Take ownership of the end-to-end process, including architecture, design, development, deployment, and operations of data pipelines, applying DevOps practices, pair programming, and other cutting-edge methodologies.

Be active, solution-oriented member of autonomous, cross-functional agile teams collaborating with Data Scientists, Machine Learning Engineers, Data Engineers, Product Owners, Back-end Engineers, Front-end Engineers, Product Analysts, and Business Intelligence teams

Demonstrate an in-depth understanding of HelloFresh’s core product and architecture, and act as ambassador for software/data solutions offering support and mentorship to colleagues

Work with state-of-the-art technologies like AWS (EMR, Glue, s3, etc), Kafka, PySpark, Kubernetes, Airflow, Prefect, Tecton, Databricks, dbt, as well as our in-house Data Pipeline tools

Leverage Claude Code and other AI tools as productivity multipliers

All other duties, as assigned

Sound a-peeling? Here's what we're looking for

Experience leading the end-to-end lifecycle of production ML systems, from architectural design to scalable deployment and monitoring.

Solid data engineering experience with the ability to design, implement, and deliver maintainable, high-quality code in Python and SQL

Hands-on experience with cloud computing and data processing technologies, including PySpark, Kubernetes, Kafka

Expertise in data modeling, relational databases (e.g., PostgreSQL), object stores (e.g., AWS S3), data platforms (Databricks)

Proven expertise in making efficient and robust data pipelines, including optimizing their performance

Passion for leveraging AI tools to streamline collaboration and execution

Passion for data quality assurance, data monitoring

Expertise in end-to-end development processes, including unit, integration & functional testing, application tuning/profiling, and continuous integration

Extensive experience with agile methodologies, with a strong focus on delivery, lean thinking, and quick iterations

Ability to continuously develop yourself and learn from your peers

Ability to collaborate and mentor team members, while also sharing practical knowledge and trends

Familiarity with e-commerce and subscription-based businesses is a plus

Interacting with back-end developers, front-end developers, product analysts, product managers and other teams around the world is very much part of our day-to-day, so communication skills are vital. We are looking for strong problem-solvers who can apply their engineering skills to a wide range of platforms and environments, while also acting as an ambassador to coach team members and stakeholders.

Let’s cut to the cheese,