Production ML Engineer: MLOps & Vertex AI

bet365; Denver (CO); On-site; USD 120,000 - 140,000; Full time

Job summary

bet365 is hiring an ML Engineer/Data Engineer to operationalize and scale models from prototype to production-grade systems. You will build reliable, automated endpoints and align with the Data Science Team Leader and US AgentOps Team Lead.

The role emphasizes rapid, maintainable software, MLOps, CI/CD for ML workflows, and real-time monitoring of data/model drift. You will collaborate with data scientists and platform engineers to accelerate deployment velocity on GCP Vertex AI and Kubernetes.

Qualifications

• Proven experience deploying ML systems to production.
• Strong Python programming with API development and testing.
• Hands-on experience with GCP and Vertex AI.
• Familiarity with containerization and Kubernetes.
• Experience with IaC tools like Terraform.
• Excellent written and verbal communication.

Responsibilities

• Owning the deployment of ML models to production and maintaining scalable, low-latency endpoints.
• Designing and maintaining CI/CD/CT pipelines for ML workflows using Vertex AI Pipelines and related GCP tools.
• Setting up automated monitoring and alerting for data drift, model drift, and system performance in real-time.
• Championing best practices for software engineering within the Data Science team, including testing and version control.
• Collaborating with the Data Science Team Leader and AgentOps Team Lead to accelerate deployment cycles.

Skills

Python programming

Production ML deployment

Communication skills

Tools

GCP

Vertex AI

Docker

Kubernetes (GKE)

Terraform

CI/CD tooling

Kafka

Pub/Sub

Job description

bet365 is hiring an ML Engineer/Data Engineer to operationalize and scale models from prototype to production-grade systems. You will build reliable, automated endpoints and align with the Data Science Team Leader and US AgentOps Team Lead.

The role emphasizes rapid, maintainable software, MLOps, CI/CD for ML workflows, and real-time monitoring of data/model drift. You will collaborate with data scientists and platform engineers to accelerate deployment velocity on GCP Vertex AI and Kubernetes.