Senior MLOps Engineer (f/m/d)

HamburgFull-timesenior

Machine Learning EngineerData

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Quick Summary

Overview

adjoe is redefining the future of mobile ads. Powered by advanced AI, first-party data and world-class engineers, we’ve perfected the offerwall experience for monetizing and scaling app publishers with solutions like Playtime – now the fastest growing rewarded advertising channel globally – driving…

Technical Tools

airflowdockerkubernetespythonadtechdeep-learningmachine-learning

Playtime is a time- and event-based ad unit that continuously rewards users with in-app currency – for the time they spend and events completed while playing mobile games. We connect advertisers to 700+ million Playtime users and serve 2bn requests per day at low latency. We ensure that all parties involved have a positive experience. Advertisers get more users for their apps. Monetizers earn revenue for users on their platforms. Users play fun games while simultaneously getting rewarded.

Our data science team powers the engine that distributes our ads. They solve multiple tasks such as developing algorithms to provide the most relevant ads for users, predicting user interests and inclinations, and dynamically adjusting pricing based on these predictions. Because the user base is very diverse we are using deep learning models that we could show to be able to serve the best ads to users.

Within the Playtime team you will be responsible for services and models that we use to provide automated solutions both for our advertisers and publishers.

Continuous Training & Automation: Design and manage continuous training (CT) and scheduling logic to ensure our models stay fresh as new data flows.

Observability & Data Quality: Build ML monitoring systems for data skew and distribution shifts, catching performance decay before it impacts our users and product KPIs.

High-Performance Deployment: Wrap deep learning models into low-latency APIs and lead load testing to ensure our services remain solid under 2bn+ daily requests, using deep-dive resource profiling to guide efficiency and optimize model performance.

ML Platform Infrastructure: Partner with the Infra team to architect a robust ML platform, providing Data Scientists with automated access to the CPU/GPU clusters they need for both development and production.

You have 5+ years in MLOps or ML Engineering, with a track record of deploying and maintaining models in high-traffic production environments.

You understand the end-to-end ML lifecycle and have a functional grasp of ML algorithms.

You are proficient in Python with experience in specialized serving frameworks like Triton, ONNX Runtime, or TF Serving for ultra-low-latency inference.

You have hands-on experience with Kubernetes, Docker, and orchestration tools like Airflow / Kubeflow to manage model workflows.

You are an expert in tracking model drift and data quality using frameworks like Evidently ensuring high-quality alerts are integrated directly into production monitoring and alerting pipelines.

You are open to relocating to Hamburg, Germany.

Plus: Experience in the AdTech industry.

Invest in Your Future: Regular feedback and our development program support your growth, helping you expand your skillset and achieve your career goals.

Easy Arrival to adjoe: From signing to settling in Hamburg, we’ve got you covered. Need a visa? No problem. Ready to build your new life and career at adjoe in Hamburg? We support every ambition—from learning German to a relocation bonus that helps you settle in and make Hamburg feel like home.

Live Your Best Life, at Work and Beyond: We work in a hybrid setup with 3 core office days, plus flexible working hours. Enjoy 30 vacation days, 3 weeks of remote work per year, and free access to an in-house gym with lots of different fitness classes and mental health support through our Employee Assistance Program (EAP).

Thrive Where You Work: Enjoy the Alster lake view from our central office with top-notch equipment, fun open spaces, and a large variety of snacks and drinks.

Join the Community! Participate in regular team and company events, including hackathons and social gatherings. We work together, and we celebrate together, too.