Platform Engineer II/III

We are seeking a Platform Engineer to architect and operate scalable compute infrastructure that powers our autonomous vehicle simulation and testing framework. You will build elastic compute systems across AWS and on-premises clusters, enabling engineering teams to rapidly iterate on autonomy algorithms through massive parallel simulation workloads.

Responsibilities:

Elastic Compute Architecture

• 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

Simulation Platform Development

• 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

Infrastructure as Code & Automation

• 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

System Operations & Reliability

• 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

Network Design & Infrastructure

• 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

Qualifications:

• 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

Preferred:

• 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

Compensation:

Level II - $113,000 - $141,000

Level III - $142,000 - $172,000