Remote Software engineering Jobs · MLflow

Deploy and monitor machine learning models in production using tools like Docker, Kubernetes, and MLflow to ensure scalability and reliability. Build and maintain data pipelines using Airflow, Spark, or Kafka to support model training and inference. Integrate ML models into business applications, collaborating with software engineers to operationalize solutions.

As a Machine Learning Engineer, you will play a pivotal role in building advanced AI systems that process and reason over complex, high-volume log data. You will design and implement intelligent agentic components, optimize data pipelines, and develop innovative approaches to AI observability and model interpretability. Working in a small, high-impact team, you will collaborate with product, infrastructure, and data teams to deliver real-time, actionable insights.

Help design and implement AI/ML systems that drive meaningful business outcomes. Contribute to the development of end-to-end ML solutions—from data preparation and modeling to deployment and performance optimization. The ideal candidate has hands-on experience in applied machine learning, strong software engineering skills, and a passion for building scalable, production-ready models. This is a high-impact role that blends research and engineering.

Block's Chargeback Risk Machine Learning team members build machine learning models and systems to precisely detect, intervene on, and reduce fraudulent activity across Block's Cash App and Square ecosystems. As part of our team, you and your work will safeguard the Cash App and Square ecosystems from financial loss and provide trustworthy and seamless financial experiences for millions of customers and sellers.