Senior Machine Learning Engineer, MLOps

What you'll do

• Automate model testing and validation for safe deployments.
• Provision and manage backend resources for AI inference services.
• Define and monitor health metrics to ensure service reliability.
• Own REST API integration between backend models and product surfaces.
• Collaborate with cross-functional teams to deliver production-ready solutions.
• Tune performance, reliability, and cost of deployed ML services in production.

What we're looking for

• 3+ years of professional software engineering experience building and operating production services.
• Experience automating testing and deployments using CI/CD tools for safe rollouts and rollbacks.
• Expertise in cloud-hosted, containerized services (e.g., Docker, Kubernetes) for provisioning resources and scaling inference workloads.
• Proficiency in building REST APIs with Python frameworks and integrating backend services with product or platform consumers.
• Strong software engineering fundamentals including version control, code quality, and maintainable, testable software practices.
• Experience with observability tooling (metrics, logging, tracing, alerting) and incident response in an on-call environment.