Job
- Level
- Erfahren
- Job Feld
- Data, Back End
- Anstellung
- Vollzeit
- Vertragsart
- Unbefristetes Dienstverhältnis
- Ort
- Berlin
- Arbeitsmodell
- Hybrid, Onsite
Job Zusammenfassung
In diesem Job entwickelst du skalierbare Echtzeit-Services in Go und Python, die Empfehlungssysteme mit Machine Learning integrieren, um personalisierte Inhalte bereitzustellen und die Systemzuverlässigkeit kontinuierlich zu optimieren.
Job Technologien
Deine Rolle im Team
- We are on the lookout for a Engineer II for our Core Recommendations Engineering squads. This role is critical to building and operating the systems that power personalized discovery at scale.
- You will own production services written in Go and Python that serve real-time recommendations across multiple surfaces, integrating tightly with machine-learning models and experimentation platforms.
- You would be responsible for delivering, enhancing and maintaining the recommendation system which is robust, scalable and observable.
- You will work closely with other engineers in the team on mainly backend engineering and few front-end related components.
- You would collaborate with data engineering, data science, product partners to translate the recommendation strategies and models into production-grade engineering solutions.
- Your squad is responsible for one of the foundational components of our customer discovery experience.
- End-to-End Recommendation System: Design, build, and operate the full recommendation flow from candidate retrieval (recall-oriented systems, embeddings, and filters), through ranking (feature enrichment, model inference, scoring), to re-ranking (business rules, diversity, freshness, and policy constraints).
- Ensure these pipelines meet strict latency, availability, and correctness requirements.
- Production-Grade Recommendation Services: Build low-latency, high-throughput services in Go and Python that expose recommendation APIs, orchestrate model inference, and integrate with feature stores, vector databases, and downstream consumers.
- System Ownership & Data Correctness: Own the lifecycle of recommendation systems, including data contracts, offline/online consistency, feature freshness, and backfills.
- Ensure correctness, reproducibility, and debuggability of recommendation outcomes.
- Operational Excellence at Scale: Operate Tier-1 recommendation services with strong observability, alerting, and incident response.
- Perform post-mortems, manage error budgets, and continuously improve reliability, tail latency, and throughput.
- Engineering Quality & Delivery Velocity: Follow strong engineering practices across Go and Python codebases, including testing strategies for ranking logic, CI/CD, safe rollouts, and performance regression detection.
- Experimentation & Iteration: Enable fast iteration through A/B testing, shadow deployments, and controlled rollouts.
- Partner with Product and Data Science to support model experimentation while maintaining system stability.
Unsere Erwartungen an dich
Qualifikationen
- You not just worry about the code but also about how this would fit into the overall eco-system.
- Owning and maintaining tier-1 services: You are ready to take the measured risks, apply prior learnings to improve the processes.
- You do not fear for responsibility if it comes with enough context about how to handle it.
- You will be touching the systems serving the high throughput live traffic.
- Go & Python Backend Expertise: You are familiar with Go and Python and worked on past projects which serve production traffic at large scale.
- Ideally into data-intensive or ML-enabled systems with strict performance requirements.
- Strong problem solving: You can take the vague problem statements to break them down into smaller chunks, propose a solution, and take it to the finish line.
- Collaborative mindset: With the guidance from senior engineers; you can balance between the short term goals and longer term solutions.
- You know how to align your personal ambitions with the team goals.
Erfahrung
- Experience of building from scratch: With some guidance/direction from the senior engineers, you should be able to convert high level requirements into production quality deliverable.
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
Engineer II, ML/Go
- Ort
- Berlin
- Arbeitsmodell
- Hybrid, Onsite
- Diversität
- Für alle Personen geeignet (m/w/d)
- Nur Englisch
- Nur Englisch erforderlich
