Senior MLOps Engineer

Das ist der Job

You'll be at the centre of our expanding Intelligence Tribe.

Darum lohnt es sich

ABOUT THE TEAM We're a passionate cross-functional team of engineers, data scientists, product manager, and an engineering manager, dedicated to all things data. ABOUT THE ROLE We are seeking a Senior MLOps Engineer to join our growing Intelligence Platform team.

You’ll work closely with data scientists, engineers, and Infrastructure team to streamline the machine learning lifecycle and bring cutting-edge solutions into production.

WHAT'S IN IT FOR YOU A Research and Development Department of 90+ of engineers, product managers and product designers in Berlin Leaders with 8+ years of experience building our promotions engine €1,000 annual learning budget, full LinkedIn Learning access, and free German language courses to boost your skills 30 days of annual leave, plus extra paid days for your birthday and moving day Home office setup budget, a monthly home office allowance Freedom to work from abroad for up to 90 days worldwide!

Talon.One is the most powerful incentives engine that unifies loyalty, promotions and gamification into one holistic platform.Backed by enterprise-grade security and scalability, Talon.One empowers companies to build personalized, profitable promotions and loyalty programs using any data.

Today, over 250 of the world’s most-loved brands including Adidas, Sephora and Carlsberg work with Talon.One to drive deeper engagement and lasting loyalty with their customers. We're enthusiastic about exploring new tools and technologies, and we thrive on brainstorming to solve challenges and apply best practices.

In this role, you will be responsible for designing, developing, and maintaining robust MLOps infrastructure and workflows that support the deployment, monitoring, and scalability of our machine learning models.

ONCE YOU ARE HERE, YOU WILL Build and maintain MLOps pipelines to automate data preparation, model training, evaluation, deployment, and monitoring of ML models and data pipelines. Design scalable infrastructure using our cloud platform and tools like Kubernetes, Docker, and Terraform.

Implement CI/CD for ML models, ensuring reproducibility, reliability, and version control. Monitor model performance and data drift in production, and implement automated retraining workflows as needed. Collaborate with data scientists and engineers to operationalize machine learning models in a secure, efficient, and scalable manner.

Maintain model registries, metadata tracking, and experiment management tools. Advocate for and help implement best practices in MLOps across the organization. Ensure compliance with security, governance, and ethical AI guidelines.

WHAT WE EXPECT YOU TO BRING TO THE TABLE 6+ years of experience in software engineering or DevOps, with at least 3+ years in MLOps or ML infrastructure roles. Experience deploying and managing machine learning systems at scale, preferably in high-availability, real-time environments with low latency and high throughput.

Experience with building or maintaining scalable ML infrastructure (e.g., CI/CD for models, auto-scaling, load balancing, blue-green deployment, canary releases, shadow testing, etc.). Strong programming skills in Python and familiarity with ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn).

Proficiency with Google Cloud Platform and infrastructure-as-code tools like Terraform. Hands-on experience with tools like Vertex AI, MLflow, Kubeflow, Airflow, or SageMaker. Experience with containerization and orchestration technologies (Docker, Kubernetes). Experience implementing monitoring and alerting systems for ML pipelines and APIs.

Mental health support with nilo.health and a discounted Urban Sports Club membership 20% company subsidy on your pension contributions Discounted BVG public transport ticket and bring along your furry friend to our dog-friendly Berlin office! Lease your ideal bike through BusinessBike #J-18808-Ljbffr