Teams at Zyphra

Designs and maintains secure, observable, scalable infrastructure for ML research and production workloads. Responsibilities include infrastructure as code, CI/CD, deployment reliability, monitoring, incident response, disaster recovery, fault tolerance, release auditability, and performance hardening. The role supports GPU clusters, cloud environments, reproducible experiments, and ML model-serving infrastructure while partnering with ML, DevOps, and infrastructure teams.

Build and operate Linux-based ML training clusters and inference cloud infrastructure. Responsibilities include access management, hardware validation, job scheduling, container orchestration, CI/CD, observability, incident response, capacity planning, autoscaling, cost tracking, and production security. The role supports heterogeneous accelerators, large-scale training, LLM serving, developer workflows, and reliable model deployments while collaborating across training, inference, product, and technical teams.

As a GTM Engineer, you'll design AI-driven workflows for sales and marketing operations, automate processes, and collaborate across teams to enhance go-to-market strategies.