Описание

We are on the lookout for a Senior Machine Learning Engineer to join the Logistics Optimization team. The Optimization Tribe's purpose is to maximize Delivery Hero's logistics performance by 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. 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.

Responsibilities

Design, build and maintain scalable ML models services, optimizing for performance and efficiency
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
Work closely with data scientists and engineers to understand their product needs and build scalable solutions
Build and enhance ML engineering tooling for Model Development, Monitoring, Serving, and Experimentation
Utilize DH cloud infrastructure built with modern technologies on popular cloud platforms to build highly available systems for multiple teams
Proactively suggest how the team can leverage new technologies and architectures to support new use cases

Requirements

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
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
Experience building new applications from scratch along with experience building quick proof of concepts (PoCs) for solving system design challenges using open-source tools
Experience in tech explorations to evaluate technologies for business problems and proposing solutions based on comprehensive pros and cons analysis
Experience in deep-diving into existing systems for investigations and improvements
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

We offer

Hybrid working model with 2 days a week in the Berlin campus
27 days holiday with an extra day on 2nd and 3rd year of service
1.000 € Educational Budget, Language Courses, Parental Support and access to the Udemy Business platform
Health Checkups, Meditation & Gym
Employee Share Purchase Plan, Sabbatical Bank, Public Transportation Ticket Discount, Life & Accident Insurance, Corporate Pension Plan
Digital Meal Vouchers and Food Vouchers
Relocation support to Berlin

Hiring process

We encourage you to let us know if you need any accommodations or specific accessibility support to ensure a smooth interview experience