bet365 is seeking a highly pragmatic, results-driven Machine Learning (ML) Engineer for its US Data team in Denver, Colorado, with a hybrid work arrangement. In this role you will build the reliable, automated infrastructure that powers the ML lifecycle, and your primary mission is to operationalize and scale models developed by the data science team from prototype to production-grade systems with high velocity. You will focus on building reliable, automated, and maintainable systems, prioritizing speed, reliability, and business value over overly complex infrastructure. You will be passionate about automation, software engineering excellence, and MLOps. You will report to the Data Science Team Leader and work closely with the US AgentOps Team Lead and the UK technical excellence center, acting as the bridge between model development and reliable platform engineering. The listed salary is USD 120,000 – 140,000 per year. Qualifications include proven experience as an ML Engineer, Data Engineer, or Software Engineer with a focus on deploying, monitoring, and scaling machine learning systems in production; strong Python programming skills; extensive experience with Google Cloud Platform (GCP) and Vertex AI; experience with Docker and Kubernetes; familiarity with IaC tools like Terraform; and experience with real-time streaming tools such as Kafka or Pub/Sub. Responsibilities include deploying ML models to production, building scalable, low-latency prediction endpoints on GCP Vertex AI, and designing CI/CD/CT pipelines for ML workflows using Vertex AI Pipelines and related tool

bet365 is seeking a highly pragmatic, results-driven Machine Learning (ML) Engineer for its US Data team in Denver, Colorado, with a hybrid work arrangement. In this role you will build the reliable, automated infrastructure that powers the ML lifecycle, and your primary mission is to operationalize and scale models developed by the data science team from prototype to production-grade systems with high velocity. You will focus on building reliable, automated, and maintainable systems, prioritizing speed, reliability, and business value over overly complex infrastructure. You will be passionate about automation, software engineering excellence, and MLOps. You will report to the Data Science Team Leader and work closely with the US AgentOps Team Lead and the UK technical excellence center, acting as the bridge between model development and reliable platform engineering. The listed salary is USD 120,000 – 140,000 per year. Qualifications include proven experience as an ML Engineer, Data Engineer, or Software Engineer with a focus on deploying, monitoring, and scaling machine learning systems in production; strong Python programming skills; extensive experience with Google Cloud Platform (GCP) and Vertex AI; experience with Docker and Kubernetes; familiarity with IaC tools like Terraform; and experience with real-time streaming tools such as Kafka or Pub/Sub. Responsibilities include deploying ML models to production, building scalable, low-latency prediction endpoints on GCP Vertex AI, and designing CI/CD/CT pipelines for ML workflows using Vertex AI Pipelines and related tool