Edge Compute Engineer @ Planet
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About Planet
Welcome to Planet. We use space to help life on Earth by designing, building, and operating the largest constellation of imaging satellites. Our cloud-based platform delivers unprecedented data used by commercial, environmental, and humanitarian sectors.
About the Role
The Edge Compute Engineer will join Planet's High Resolution team to develop and operate critical compute software supporting end-to-end imaging operations. You will design robust, reproducible deployment systems for diverse customer environments and partner with cross-functional teams to troubleshoot distributed systems.
Impact You'll Own
- Build and deploy software in customer environments
- Own deployments, service orchestration, and cross-platform documentation
- Scale architectures ensuring service availability
- Improve reliability through testing, troubleshooting, and failure analysis
- Participate in on-call rotations for operational excellence
What You Bring
Bachelor’s degree in Computer Science or similar with 6+ years experience in cloud-native service engineering. Proficiency with tools like Kubernetes (K3s, RKE2, TalOS), Terraform, Ansible, Helm, and Python is required. Experience with hardware-level on-prem compute and platform optimization is essential, along with excellent communication skills.
What Makes You Stand Out
- Experience with geospatial data and GDAL, NumPy
- Exposure to CUDA-based GPU programming
- Security expertise in sensitive, air-gapped environments
Additional Information
This is a full-time, remote position based in the United States with occasional on-site expectations if near an office. The role includes comprehensive benefits and a competitive salary structure based on experience and location.
Key skills/competency
- Edge Compute
- Deployment
- Cloud-native
- Kubernetes
- Terraform
- Ansible
- Python
- Distributed Systems
- Scalability
- Security
How to Get Hired at Planet
🎯 Tips for Getting Hired
- Research Planet's culture: Understand their mission and satellite technologies.
- Customize your resume: Highlight cloud and compute expertise.
- Prepare for interviews: Review distributed systems and tools.
- Showcase real projects: Demonstrate deployment and scalability success.