Teams at MNTN

Design, provision, and operate cloud infrastructure (primarily GCP/GKE) and Kubernetes platform tooling. Build GitOps-driven automation, CI/CD pipelines, IDP/self-service developer tooling, cost optimization, observability, security controls, and runbooks to improve reliability and developer velocity.

Build and operationalize machine learning models for large-scale advertising optimization. Responsibilities include designing high-volume services, developing data solutions, training and evaluating models, improving calibration and guardrails, creating offline and online evaluation workflows, and monitoring production systems. The role requires collaboration with product and engineering teams, ownership of reliability and performance, participation in on-call rotations, and deploying scalable, cost-effective ML solutions.

Develop and support Kotlin APIs and high-volume distributed services for audience targeting and machine learning products. Work with Rust, PySpark, Kafka, relational databases, and hundreds of terabytes of daily data. Build reliable systems at scale, optimize existing products, collaborate with product and project leaders, and contribute to engineering culture. The role requires strong JVM-language development, SQL and database expertise, microservices experience, cloud infrastructure knowledge, and effective use of AI coding tools.