Staff Platform Machine Learning Engineer - Engine

About the Role

Gen Digital is seeking a Staff Platform Machine Learning Engineer to design and operate infrastructure supporting ML training, deployment, and inference workloads for Engine by Gen, a fintech platform serving millions of consumers. You'll own critical platform systems that enable data scientists and engineers to build, deploy, and run machine learning models at scale, with direct impact on financial products and personalized content delivery.

Responsibilities

• Design, build, and maintain infrastructure supporting ML training, deployment, and inference workloads
• Own and improve CI/CD pipelines, infrastructure-as-code, observability, and operational tooling for ML systems
• Operate and evolve production systems with focus on reliability, performance, and cost efficiency
• Build and maintain Kubernetes and cloud-based services that support model execution and data workflows
• Partner with data scientists and engineers to support model deployment and address operational needs
• Improve developer workflows through automation, tooling, and platform abstractions
• Participate in on-call rotation and maintain operational ownership for assigned platform components

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or related field
• 7+ years of experience in software engineering, platform engineering, DevOps, or SRE roles
• Strong systems engineering background with demonstrated production operations experience
• Substantial experience with backend or platform services
• Hands-on expertise with cloud infrastructure and tooling (AWS, Docker, Kubernetes, Terraform, CI/CD, monitoring)
• Proven experience operating distributed systems in production environments
• Experience with machine learning infrastructure, model serving, or data platforms (strong plus)
• Strong problem-solving skills and operations-first mindset
• Ability to manage complex problems in a fast-paced, high-tech environment

Benefits

• Flexible working options
• Competitive pay
• Well-being programs
• Time off and career growth support