Platform Engineer II/III

Zone 5 Technologies is redefining unmanned aircraft systems with a focus on innovative autonomous solutions. They are seeking a Platform Engineer to design and operate scalable compute infrastructure that powers their autonomous vehicle simulation and testing framework, enabling rapid iteration on autonomy algorithms through parallel simulation workloads.

Responsibilities:

• Design and implement auto-scaling compute infrastructure for simulation workloads using cloud platforms
• Build and maintain on-premises GPU and CPU clusters for simulation and machine learning training
• Architect hybrid cloud solutions that optimize cost and performance across cloud and local compute resources
• Implement job scheduling and orchestration systems using Kubernetes for thousands of concurrent simulations
• Design storage solutions for large-scale simulation data, logs, and artifacts using cloud and local storage systems
• Deploy and maintain robotics simulation environments at scale
• Build CI/CD pipelines for automated simulation testing of autonomy software
• Create infrastructure for distributed parameter sweeps, Monte Carlo testing, and regression suites
• Develop monitoring and observability systems for simulation fleet health and resource utilization
• Implement data pipelines for simulation results ingestion, analysis, and visualization
• Write and maintain infrastructure as code for reproducible infrastructure deployment
• Build automation tools and CLI utilities to simplify developer access to compute resources
• Implement GitOps workflows for infrastructure changes and configuration management
• Create self-service interfaces for engineers to launch and manage simulation jobs
• Develop cost monitoring and optimization strategies for cloud and on-prem resources
• Monitor and optimize infrastructure performance, reliability, and cost efficiency
• Troubleshoot complex distributed systems issues across networking, storage, and compute layers
• Implement backup, disaster recovery, and business continuity strategies
• Maintain security best practices including IAM, secrets management, and network isolation
• Collaborate with autonomy, ML, and robotics teams to understand compute requirements and optimize workflows
• Design and implement network architectures for distributed simulation workloads across AWS and on-premises environments
• Configure VPCs, subnets, security groups, and routing for secure, high-performance compute clusters
• Establish hybrid cloud connectivity (VPN, Direct Connect, site-to-site tunnels) between on-premises and cloud resources
• Optimize network performance for large data transfers, multi-node communication, and distributed workloads
• Support internal infrastructure network design and provide technical guidance to engineering programs
• Troubleshoot network issues including latency, packet loss, and connectivity problems across distributed systems

Requirements:

• Bachelor's in Computer Science, Software Engineering, or related technical field – equivalent industry experience also welcome
• 2-5+ years of experience in platform engineering, DevOps, SRE, or cloud infrastructure roles
• Strong hands-on experience with Kubernetes for container orchestration and workload management
• Experience with cloud computing platforms and services (compute, storage, networking)
• Deep understanding of Linux system administration and troubleshooting
• Strong networking fundamentals including TCP/IP, routing, DNS, VPNs, and security
• Understanding of infrastructure as code principles and configuration management
• Proficiency in scripting and automation (Python, Bash, or similar)
• Experience building and maintaining CI/CD pipelines
• Solid grasp of distributed systems concepts, job scheduling, and resource management
• Ability to design infrastructure from first principles and make architectural decisions
• Experience building infrastructure for simulation, robotics, or autonomous systems workloads
• Understanding of GPU computing and accelerated workload management
• Knowledge of job scheduling systems for batch and parallel workloads
• Experience managing on-premises clusters and hybrid cloud architectures
• Familiarity with robotics middleware (ROS/ROS2) or simulation platforms
• Understanding of cost optimization for compute-intensive workloads
• Experience with monitoring, logging, and observability systems
• Knowledge of containerization technologies and image management
• Background in data engineering, MLOps, or machine learning infrastructure
• Experience with network performance analysis and troubleshooting
• Understanding of software-defined networking and network automation
• Familiarity with security compliance requirements in aerospace/defense environments