Senior MLOps Engineer (f/m/d)

MLOps at production scale. You have 5+ years in MLOps or ML Engineering with a track record of deploying and maintaining models in high-traffic environments. At adjoe, that means keeping models fresh and performant across 2 billion+ daily requests, where decay in model quality directly impacts user experience and advertiser KPIs.

Continuous Training & Automation. You design and manage CT pipelines and scheduling logic to ensure models stay current as new data flows in. You understand the end-to-end ML lifecycle well enough to know when a model needs retraining.

Observability is part of the system, not an afterthought. You build monitoring systems that catch data skew, distribution shifts, and performance decay in production, using frameworks like Evidently, with alerts integrated directly into production pipelines.

Low-latency serving under heavy load. You wrap deep learning models into production APIs and lead load testing to validate performance at scale. You're proficient in serving frameworks like Triton, ONNX Runtime, or TF Serving, and use deep-dive resource profiling to guide efficiency and optimization.

ML platform ownership. You work with infrastructure teams to architect the ML platform, automated access to CPU/GPU clusters via Kubernetes, Docker, and orchestration tools like Airflow or Kubeflow, so data scientists can focus on models, not infrastructure. 

Plus: AdTech industry background. You understand how ad delivery systems work and the business logic underneath.

Go Big. Own projects with impact on 770M users and push adtech boundaries.

Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum.

Be Direct. Solve problems openly and collaborate across teams.

Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other.  

Have Fun. Celebrate wins, enjoy daily victories, and bring your energy.