(Senior) ML Platform Engineer (w/m/d)

at  Billie

We are Billie, the leading provider of Buy Now, Pay Later (BNPL) payment methods for businesses, offering B2B companies innovative digital payment services and modern checkout solutions. We are to create a new standard for business payments and have made it our mission to simplify the purchasing experience for all businesses making it a tool for growth. Our solutions are based on proprietary, machine-learning-supported risk models, fully digitized processes and a highly scalable tech platform. This makes us a deep-tech company building financial products, not the other way around. We love building simple and elegant solutions and we strive for automation and scalability.

WHO WE ARE LOOKING FOR:

• Extensive experience with machine learning workflows and MLOps tools such as Metaflow and MLflow
• Strong knowledge of model deployment, serving, and monitoring using tools like AWS SageMaker, KServe, Seldon Core
• Proficiency in designing and implementing model deployment pipelines using Github Actions, ArgoCD, or similar tools
• Experience with orchestration tools such as Airflow, ArgoCD, Prefect
• Familiarity with data versioning, data governance practices, and model versioning
• Understanding of reproducibility and experimentation using tools like MLflow or Weights & Biases
• Knowledge of model training and inference using popular frameworks like Scikit-learn (TensorFlow or PyTorch is a plus)
• Excellent collaboration skills, particularly in working with data scientists on model deployment and optimization

Join our dynamic team in Berlin as a Senior MLOps Engineer and play a crucial role in shaping the future of our ML infrastructure. You’ll be responsible for designing, building, and maintaining scalable and resilient machine learning pipelines that support real-time and batch model deployment and monitoring. Your expertise will be key in supporting various AI and machine learning initiatives across the organization, making a real-time, real-life impact on our business.
What you will be working on: