Steven-Greenhouse Logo

Steven-Greenhouse

Platform Engineer II/III

Posted Yesterday
Be an Early Applicant
Easy Apply
Remote
Hiring Remotely in United States
113K-172K Annually
Mid level
Easy Apply
Remote
Hiring Remotely in United States
113K-172K Annually
Mid level
Design, build, and operate scalable hybrid compute infrastructure (cloud and on-prem) for large-scale autonomous vehicle simulations. Implement Kubernetes orchestration, job scheduling, CI/CD, IaC/GitOps, monitoring, networking, storage, and automation to support massive parallel simulation workloads and ML training. Collaborate with autonomy, ML, and robotics teams to optimize performance, reliability, and cost.
The summary above was generated by AI

At Zone 5 Technologies, we're redefining what's possible in unmanned aircraft systems. Our team of engineers and innovators is developing cutting-edge autonomous solutions that push the boundaries of UAS technology - solving complex challenges that matter.

We're building the future of UAS capabilities, and we're looking for exceptional talent to join us. If you're driven by hard problems, energized by rapid innovation, and ready to make an impact on next-generation flight systems, you belong here.

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

Pay range for this role
$113,000$172,000 USD

What's in it for you:

Benefits: 

  • Competitive total compensation package 
  • Comprehensive benefit package options include medical, dental, vision, life, and more.
  • 401k with company-match 
  • 4 weeks of paid time off each year
  • 12 annual company holidays

Why Join Zone 5 Technologies?

  • Innovative Environment: Work on cutting-edge technology that is shaping the future of defense and aerospace.
  • Collaborative Culture: Join a team of passionate professionals dedicated to pushing the boundaries of what’s possible.
  • Career Growth: Opportunities for professional development and career advancement.

If you are passionate about unmanned aircraft technology and want to be a part of a dynamic and growing company, we would love to hear from you. Apply today and join the Zone 5 Technologies team! 

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.

Zone 5 Technologies is a federal contractor and participates in E-Verify to confirm employment eligibility. As required by law, we will verify the identity and employment authorization of all new employees using the E-Verify system. Learn more about your rights and responsibilities under E-Verify: https://www.e-verify.gov.

Similar Jobs

2 Hours Ago
Easy Apply
Remote
United States
Easy Apply
118K-190K Annually
Senior level
118K-190K Annually
Senior level
Financial Services
Lead Support Readiness and Quality Intelligence for global customer support. Build and run onboarding, upskilling, QA/audit, AI-augmented review, and coaching frameworks. Drive AI-native transformation, cross-functional alignment, KPI measurement (AHT, CSAT, time-to-proficiency), and translate quality signals into actionable enablement to improve agent performance and business outcomes.
2 Hours Ago
Easy Apply
Remote
United States
Easy Apply
118K-179K Annually
Senior level
118K-179K Annually
Senior level
Financial Services
Design, build, and operate large-scale data pipelines and Spark/PySpark workflows; architect and evolve Samsara's data platform; build MCP servers and AI-agent tooling; optimize performance, ensure data quality and observability; mentor engineers and lead cross-functional projects to deliver scalable data products for analytics and business teams.
Top Skills: Ai AgentsApache IcebergApi GatewayAuroraAWSAws CloudwatchAws LambdaAws RdsAws Secrets ManagerAzureDatabricksDatadogDbtFivetranGCPGoogle BigqueryLlmsMcp (Model Context Protocol)Ms Sql ServerMySQLNetSuiteOraclePostgresPysparkPythonS3SalesforceSnowflakeSnsSparkSplunkSQLSqs
2 Hours Ago
Remote
United States
27-38 Hourly
Junior
27-38 Hourly
Junior
Digital Media • News + Entertainment
Review and package home equity loan applications, maintain a pipeline of 30–50 loans, gather and verify borrower documentation, communicate with borrowers, loan officers, underwriters, closers and third parties, ensure compliance with mortgage and Fannie Mae guidelines, manage broker channel fulfillment, and meet closing and lock deadlines using Encompass LOS.
Top Skills: Encompass Los

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account