Senior Machine Learning Engineer (Vendor Data)

Job description

Job Description

Be our next Hero! - Join the world’s leading local delivery platform.

We are looking for a Senior Machine Learning Engineer - Vendor Data (all genders) to join the Vendor Data  tribe in our mission to deliver consistently amazing experiences.

As part of our Vendor Team, you’ll be the driving force behind the success of thousands of restaurants, shops, and local businesses.

Your contributions will empower vendors with advanced tools to manage their operations, boosting their visibility and reach.

Every feature you help build will create growth opportunities for businesses of all sizes, strengthening Delivery Hero’s ecosystem and impact.

The Vendor Data tribe’s mission is to drive innovation, insight-driven decision making and to solve business problems through a culture of excellence and openness.

The tribe comprises teams of skilled analysts, engineers, and scientists working together to deliver data solutions covering a host of business opportunities across all of Delivery Hero’s 70+ markets.

Your contributions will empower vendors with advanced tools to manage their operations, boosting their visibility and reach.

We are looking for a talented and motivated Senior Machine Learning Engineer (all genders) to work with best-in-class data science and AI models to drive our fundamental shift to machine learning in the Vendor vertical at Delivery Hero.

You will be working with a team of ML Engineers and Data Scientists deploying advanced ML services to solve complex problems, delivering revenue for Delivery Hero at the frontline of our profitability journey. 

If you're a builder in machine learning who is hungry for a new adventure, an international workplace is waiting for you in the heart of Berlin!

Your mission:

• Drive the design, build and maintain large-scale machine learning systems, ensuring they align with the Vendor  strategic product goals, while optimising for performance and efficiency

• Architect scalable, reliable, and cost-efficient ML infrastructure to manage the entire ML lifecycle at scale.

• Set and uphold best practices for productionising ML, including monitoring, testing, reproducibility, and responsible AI practices.

• Collaborate with product, engineering, analysts, and data science teams to understand their needs and build solutions that optimise their workflows.

• Leverage cloud  technologies to build reliable, efficient and robust systems for multiple teams.
  
  Influence by proactively suggesting how to leverage new technologies to support multiple downstream use cases.

• Raise the technical bar and foster a culture of excellence in ML engineering.

• Stay ahead of industry and academic trends, evaluating and introducing emerging technologies and methodologies that can shape Delivery Hero’s future ML capabilities.

What you'll need to be successful:

• Expert knowledge of data management, storage, and best MLOps and DataOps practices to enable performant and cost-efficient ML systems at scale.

• Deep expertise with modern ML frameworks and libraries (e.g. TensorFlow, PyTorch) and the ability to guide adoption of best practices across diverse ML use cases.

• Experience in designing, deploying, and operating large-scale machine learning systems in production, with a track record of delivering high-impact solutions.

• Hands-on experience with cloud platforms and distributed infrastructure (AWS, GCP, Azure) and proficiency in containerisation and orchestration technologies (eg Docker, Kubernetes) for building resilient ML services. 

• Experience with CI/CD pipelines and commonly used tools in ML Engineering such as Metaflow, MLflow, Airflow, Grafana, and similar.

• Strong systems-level problem-solving skills, with the ability to balance performance, scalability, maintainability, and business impact.

• Great communication and collaboration skills, with the ability to partner effectively across product, engineering, and business stakeholders.

Highly desirable:

• Proven ability to design and scale ML systems under strict latency, throughput, and cost constraints, balancing innovation with operational excellence.

• Demonstrated impact in translating advanced research into production systems that drive measurable business outcomes.

What's in it for you?

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 & Bicycle Subsidy

• 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, Food Vouchers, Corporate Discounts.
  
  Courses.

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 include it in your application.

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

Required Skill Profession

Computer Occupations