Job
- Level
- Senior
- Job Feld
- Data
- Anstellung
- Vollzeit
- Vertragsart
- Unbefristetes Dienstverhältnis
- Ort
- Berlin
- Arbeitsmodell
- Hybrid, Onsite
Job Zusammenfassung
In dieser Rolle entwickelst du leistungsstarke Machine-Learning-Modelle zur Optimierung von Logistikprozessen, baust robuste Infrastruktur für Datenfeeds auf und arbeitest eng mit Data Scientists zusammen, um Echtzeit-Lösungen zu schaffen.
Job Technologien
Deine Rolle im Team
- 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.
- 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.
Unsere Erwartungen an dich
Qualifikationen
- Communication Skills: Fluency in English. Clarity in communication, both written and verbal.
- Prior knowledge of public cloud platforms (AWS, Google Cloud or equivalent).
- Knowledge of containerization and orchestration tools like Docker, Kubernetes, and Helm.
Erfahrung
- 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.
- Nice to Have Experience with ML tools like Metaflow, Airflow, MLflow, Argo Workflows, and Cloud Notebooks, etc.
- Experience with CI/CD pipelines and Infrastructure as Code (Terraform or equivalent).
Unser Angebot
- 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.
Benefits
Essen & Trinken
Work-Life-Integration
Gesundheit, Fitness & Fun
Themen mit denen du dich im Job beschäftigst
Job Standorte
Das ist dein Arbeitgeber
Delivery Hero SE
Niklas Östberg gründete Delivery Hero im Mai 2011 und startete seine Reise, um ein führendes global agierendes Unternehmen im Bereich Online-Essensbestellungen aufzubauen. Sein Gründungsteam, das mit Mitgliedern von Team Europe vervollständigt wurde, teilte sich Jahrzehnte an Wissen über die Arbeit mit Internetunternehmen. Genauso wichtig war jedoch, dass sie eine Vision für die Zukunft der Online-Essensbestellung teilten. Gemeinsam mit einem ausgewählten und leidenschaftlichen Team gelang es ihnen tatsächlich, das Geschäft auf die heutige Stufe zu katapultieren.
Description
- Gründungsjahr
- 2011
- Sprachen
- Englisch
- Unternehmenstyp
- Etablierte Firma
- Arbeitsmodell
- Hybrid, Onsite
- Branche
- Handel
Arbeitgeber-Reviews
von devworkplaces.com
Gesamt
(1 Bewertung)3.2
Career Growth
3.2Culture
3.2Engineering
2.7Workingconditions
3.8
Senior Machine Learning Engineer
- Ort
- Berlin
- Arbeitsmodell
- Hybrid, Onsite
- Diversität
- Für alle Personen geeignet (m/w/d)
- Nur Englisch
- Nur Englisch erforderlich
