An engineering degree in a related field, such as computer science or cloud architecture, or equivalent working experience.
Extensive hands-on experience with Kubernetes in production multi-cloud environments.
Proficiency with Helm for Kubernetes package management and deployment orchestration.
Deep expertise with at least two major cloud providers among AWS, GCP, and Azure.
Strong proficiency in infrastructure as code.
Solid programming skills in Rust, Go, C++, or Python.
Experience architecting and operating distributed systems at scale.
Advanced knowledge of containerization technologies, including Docker and Containerd.
A strong understanding of cloud networking, security, and compliance requirements.
Experience with GPU orchestration and high-performance computing workloads.
Linux systems administration and performance tuning expertise.
Responsibilities
Architect multi-cloud infrastructure strategies across AWS and GCP for optimal performance and cost.
Design and implement scheduling and orchestration for managing thousands of concurrent simulation workloads on Kubernetes.
Build infrastructure as code solutions to ensure reproducible and scalable deployments.
Optimize cloud resource allocation for GPU-intensive rendering and compute workloads.
Implement auto-scaling strategies that respond to dynamic simulation demands.
Create multi-region deployment architectures for high platform availability.
Build comprehensive monitoring and alerting systems for platform health and performance.
Develop disaster recovery and business continuity strategies for mission-critical simulations.
Interface directly with enterprise customers to ensure the platform meets their infrastructure requirements.
Implement security best practices and compliance frameworks across all cloud environments.
Collaborate with engineering teams to optimize platform architecture for their specific needs.
Desired Qualifications
Experience with simulation or rendering infrastructure.
Background in operating platforms for autonomous systems or robotics.
As a Platform Engineer at Zeromatter, you'll build and scale the cloud infrastructure that powers our revolutionary simulation platform across the world's leading robotics companies. You'll orchestrate massive computational resources across multiple cloud providers, ensuring our platform delivers photorealistic simulations with uncompromising reliability and performance. This role offers the rare opportunity to architect infrastructure at the bleeding edge of what's possible, enabling autonomous systems to be developed, tested, and validated in virtual worlds indistinguishable from reality.
Responsibilities
Architect multi-cloud infrastructure strategies across AWS and GCP for optimal performance and cost.
Design and implement scheduling and orchestration for managing thousands of concurrent simulations workloads on Kubernetes.
Build infrastructure as code solutions to ensure reproducible and scalable deployments.
Optimize cloud resource allocation for GPU-intensive rendering and compute workloads.
Implement auto-scaling strategies that respond to dynamic simulation demands.
Create multi-region deployment architectures for high platform availability.
Build comprehensive monitoring and alerting systems for platform health and performance.
Develop disaster recovery and business continuity strategies for mission-critical simulations.
Interface directly with enterprise customers to ensure platform meets their infrastructure requirements.
Implement security best practices and compliance frameworks across all cloud environments.
Collaborate with engineering teams to optimize platform architecture for their specific needs.
Qualifications
Engineering degree in a related field (e.g. computer science, cloud architecture) or equivalent working experience.
Extensive hands-on experience with Kubernetes in production multi-cloud environments.
Proficiency with Helm for Kubernetes package management and deployment orchestration.
Deep expertise with at least two major cloud providers (AWS, GCP, Azure).
Strong proficiency in infrastructure as code.
Solid programming skills in languages like Rust, Go, C++, and Python.
Experience architecting and operating distributed systems at scale.
Advanced knowledge of containerization technologies (Docker, Containerd).
Strong understanding of cloud networking, security, and compliance requirements.
Experience with GPU orchestration and high-performance computing workloads.
Linux systems administration and performance tuning expertise.
Bonus: Experience with simulation or rendering infrastructure.
Bonus: Background in operating platforms for autonomous systems or robotics.