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Senior Machine Learning Engineer - (Logistics, Optimization) at Delivery Hero · Katori

Asks for

The ad says“ML and DS Experience: You have significant experience (ideally 3+ years) designing and implementing diverse machine learning models (e.g., regression, classification, tree-based ensembles) to solve real-world business problems, backed by a strong theoretical foundation in statistics and probability.”
The ad says“ML Engineering Experience: Prior experience (Ideally 4+ years) in ML engineering or MLOps and familiar with the ML engineering ecosystem tools used for Model serving, training, experimentation, and feature engineering. Have experience building infrastructure around machine learning pipelines leveraging modern tools with hands-on experience in modern programming languages such as Python”
The ad says“ML Engineering Experience: Prior experience (Ideally 4+ years) in ML engineering or MLOps and familiar with the ML engineering ecosystem tools used for Model serving, training, experimentation, and feature engineering. Have experience building infrastructure around machine learning pipelines leveraging modern tools with hands-on experience in modern programming languages such as Python”
The ad says“ML Engineering Experience: Prior experience (Ideally 4+ years) in ML engineering or MLOps and familiar with the ML engineering ecosystem tools used for Model serving, training, experimentation, and feature engineering. Have experience building infrastructure around machine learning pipelines leveraging modern tools with hands-on experience in modern programming languages such as Python”
The ad says“ML Engineering Experience: Prior experience (Ideally 4+ years) in ML engineering or MLOps and familiar with the ML engineering ecosystem tools used for Model serving, training, experimentation, and feature engineering. Have experience building infrastructure around machine learning pipelines leveraging modern tools with hands-on experience in modern programming languages such as Python”
The ad says“ML Engineering Experience: Prior experience (Ideally 4+ years) in ML engineering or MLOps and familiar with the ML engineering ecosystem tools used for Model serving, training, experimentation, and feature engineering. Have experience building infrastructure around machine learning pipelines leveraging modern tools with hands-on experience in modern programming languages such as Python”
The ad says“ML Engineering Experience: Prior experience (Ideally 4+ years) in ML engineering or MLOps and familiar with the ML engineering ecosystem tools used for Model serving, training, experimentation, and feature engineering. Have experience building infrastructure around machine learning pipelines leveraging modern tools with hands-on experience in modern programming languages such as Python”
The ad says“ML and DS Experience: You have significant experience (ideally 3+ years) designing and implementing diverse machine learning models (e.g., regression, classification, tree-based ensembles) to solve real-world business problems, backed by a strong theoretical foundation in statistics and probability.”
The ad says“ML Engineering Experience: Prior experience (Ideally 4+ years) in ML engineering or MLOps and familiar with the ML engineering ecosystem tools used for Model serving, training, experimentation, and feature engineering. Have experience building infrastructure around machine learning pipelines leveraging modern tools with hands-on experience in modern programming languages such as Python”
The ad says“ML and DS Experience: You have significant experience (ideally 3+ years) designing and implementing diverse machine learning models (e.g., regression, classification, tree-based ensembles) to solve real-world business problems, backed by a strong theoretical foundation in statistics and probability.”
The ad says“ML and DS Experience: You have significant experience (ideally 3+ years) designing and implementing diverse machine learning models (e.g., regression, classification, tree-based ensembles) to solve real-world business problems, backed by a strong theoretical foundation in statistics and probability.”
The ad says“ML and DS Experience: You have significant experience (ideally 3+ years) designing and implementing diverse machine learning models (e.g., regression, classification, tree-based ensembles) to solve real-world business problems, backed by a strong theoretical foundation in statistics and probability.”

Company Description

As the world’s pioneering local delivery platform, our mission is to deliver an amazing experience, fast, easy, and to your door. We operate in around 65 countries worldwide, powered by tech, designed by people. As one of Europe’s largest tech platforms, headquartered in Berlin, Germany, Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017 and is part of the MDAX stock market index. We push hard, learn quickly and stay human along the way. It’s this wonderful mix of high performance and real community that makes Delivery Hero a place where ambition and belonging grow side by side. If you’re curious, collaborative and ready to dive deep into meaningful work, you’ll fit right in.

Job Description

We are on the lookout for a Senior Machine Learning Engineer to join the Logistics Optimization team on our journey to always deliver amazing experiences.

The Optimization Tribe's purpose is to maximize Delivery Hero's logistics performance. We achieve this by owning and continuously improving the sophisticated algorithm that solves the real-time vehicle routing problem, assigning orders efficiently every second across the world. This directly impacts DH's core efficiency and customer satisfaction KPIs, influencing decisions for stakeholders from Operations to Product.

As an ML Engineer, your value lies in tackling the problems at scale head-on and building ML models and products which shape the algorithm's logic and decisions to meet our long-term goals of best-in-class efficiency and service, making a tangible impact across the Delivery Hero network. Are you ready to take your Machine Learning Engineering and Data Science skills to the next level and make a tangible impact on millions of users worldwide?

In this role you will,

Build and Maintain: Design, build and maintain scalable ML models services, optimizing for performance and efficiency.
Design Robust Architecture: Build the infrastructure that powers critical model inputs fed every minute to the dispatch algorithm which shapes experiences for millions of customers across the globe, every single day.
Collaborate and Optimize: Work closely with data scientists and engineers to understand their product needs and build scalable solutions.
Develop Tooling: Build and enhance ML engineering tooling for Model Development, Monitoring, Serving, and Experimentation.
Leverage Cloud: Utilize DH cloud infrastructure built with modern technologies on popular cloud platforms to build highly available systems for multiple teams.
Innovate and Suggest: Proactively suggest how the team can leverage new technologies and architectures to support new use cases.

Qualifications

ML Engineering Experience: Prior experience (Ideally 4+ years) in ML engineering or MLOps and familiar with the ML engineering ecosystem tools used for Model serving, training, experimentation, and feature engineering. Have experience building infrastructure around machine learning pipelines leveraging modern tools with hands-on experience in modern programming languages such as Python
ML and DS Experience: You have significant experience (ideally 3+ years) designing and implementing diverse machine learning models (e.g., regression, classification, tree-based ensembles) to solve real-world business problems, backed by a strong theoretical foundation in statistics and probability.
Application Development: Experience building new applications from scratch along with experience building quick proof of concepts (PoCs) for solving system design challenges using open-source tools.
Technical Evaluation: Experience in tech explorations to evaluate technologies for business problems and proposing solutions based on comprehensive pros and cons analysis.
System Analysis: Experience in deep-diving into existing systems for investigations and improvements.
Communication Skills: Fluency in English. Clarity in communication, both written and verbal.

Nice to Have

Experience with ML tools like Metaflow, Airflow, MLflow, Argo Workflows, and Cloud Notebooks, etc
Prior knowledge of public cloud platforms (AWS, Google Cloud or equivalent).
Experience with CI/CD pipelines and Infrastructure as Code (Terraform or equivalent).
Knowledge of containerization and orchestration tools like Docker, Kubernetes, and Helm.

Additional Information

Ensuring you and all our Heroes are looked after, happy, and healthy is always on the menu. Because if you’re in good shape, then we’re in good shape.

Make the most of our hybrid working model and join the team for face-to-face connection and collaboration in our beautiful Berlin campus 2 days a week
We offer 27 days holiday with an extra day on 2nd and 3rd year of service
We will support you in developing yourself and your career growth opportunities: 1.000 € Educational Budget, Language Courses, Parental Support and access to the Udemy Business platform to explore a variety of online courses.
Get moving and release those wonderful, mind-boosting endorphins: Health Checkups, Meditation & Gym.
Cash. Dough. Cheddar. Whatever you call it, we’ll help you with it: Employee Share Purchase Plan, Sabbatical Bank, Public Transportation Ticket Discount, Life & Accident Insurance, Corporate Pension Plan
The power of getting together over some food is unrivaled. Here are a few ways to help you do that. All the yum: Digital Meal Vouchers and Food Vouchers.
Wondering what relocating to Berlin is like? In this article, we’ve put together 10 things you should know about moving to Berlin and how Delivery Hero can support you. You can also visit our relocation hub and check out more information about moving to Berlin.
Ready to prepare for your interview? Check out the list of the 5 most common interview questions and answers created in collaboration with our recruiters.

Ready to join our team? If you’re excited to grow, collaborate and be part of the world’s leading delivery platform, we’d love to hear from you. Apply today!

We believe diversity and inclusion are key to creating not only an exciting product, but also an amazing customer and employee experience. Fostering this starts with hiring - therefore we do not discriminate on the basis of racial identities, religious beliefs, color, national origin, gender identities or expressions, sexual orientations, age, marital or disability statuses, or any other aspect that makes you, you.

We encourage you to let us know if you need any accommodations or specific accessibility support to ensure a smooth interview experience—just let us know with an email to our Inclusion Officer at inclusion@deliveryhero.com.

Severely disabled applicants with equal qualifications will be given preferential consideration.

You're welcome to share your pronouns (he/she/they) right from the start so we can address you respectfully from our first contact.