Senior Applied Machine Learning Engineer (m/f/d)

Our mission is to turn beautiful moments into lasting memories.

celebrate is a brand group with the mission to turn beautiful moments into lasting memories throughout Europe: with high quality stationery, photo products and special gift items.

We’re looking for a Senior Applied Machine Learning Engineer (m/f/d) to join our Platform Team (5 Full Stack Engineers) and take ownership of our growing AI Platform — the foundation that connects machine learning models with real product experiences across our brands.

In this role, you will be the team’s ML expert, responsible for bringing new models into production, ensuring scalability and efficiency, and shaping how AI powers personalized user experiences at celebrate company.

The position is available remotely within Germany.

Your role

• Take end-to-end ownership of the AI Platform, bridging product ideas into deployable, high-performing ML models that process and generate visual and textual content

• Evaluate, deploy, and maintain Deep Learning models across multiple modalities to power intelligent product features

• Build reliable and highly observable systems that integrate and use machine learning models orchestrated by the AI Platform

• Collaborate closely with Full Stack Engineers and Product Managers to continuously improve infrastructure and translate feature requests into production-ready solutions

Tech-Stack

• Machine Learning & Frameworks: PyTorch, TorchVision, OpenCV, Pillow

• Infrastructure & Cloud: AWS, containerization and orchestration with Docker and Kubernetes, Infrastructure-as-Code with AWS CDK

• Model Serving & APIs: FastAPI, ZenML for scalable model deployment and service integration

• Monitoring & Observability: Prometheus, Grafana, OpenTelemetry for model performance and system health tracking

Your benefits 

• We value flexibility: Flexible remote work, part-time options, modern hardware (Macbooks), collaborative office spaces (flex desks)

• We embrace new work: Agile working, fair pay, competency- and leadership models

• We care for your well-being: Nilo.health, workations, sabbaticals, 30 days paid vacation

• We want to grow with you: Internal development, coaching, regular feedback- and growth processes, flexible external learning

• We are one team: Office meals, (voluntary) events, remote team building, furry office friends and exclusive family & friends discounts

Your profile

• At least 4 years of professional experience as a Machine Learning Engineer, Applied Scientist, or MLOps Engineer — ideally with end-to-end responsibility for ML model development and deployment

• Strong expertise in selecting, deploying, and evaluating Deep Learning models with various modalities using PyTorch and cloud-based ML infrastructure

• Fluency in English (written and spoken) required for daily operations and team collaboration

Your mindset

• Pragmatic – You build practical, reliable solutions that balance performance, cost, and complexity.

• Collaborative – You communicate openly, share knowledge, and work closely with engineers, data scientists, and product teams.

• Ownership-driven – You take full responsibility from concept to deployment and ensure lasting quality in production.

About celebrate company

celebrate company group consists of the brands Atelier Rosemood, celebrate apps, celebrate digital printing, faireparterie, kartenmacherei and mintkind.

Together, we comprise e-commerce businesses, production facilities and other digital services focused on turning beautiful moments into lasting memories across Europe. As New Work pioneers, we have created a people-focused organization, based on trust, self-organization and flexibility.

Ready to apply? 

We're excited to meet you! Apply now via our online application. Don't have a CV at hand? We're fine if you add the link to your Linkedin profile to your application.

For further questions, get in touch with Mario (Junior Talent Acquisition Manager).

E-Mail: mario.stenske@celebrate.company

Please note that we do not accept applications via e-mail.