Software Engineer
Backend
Posted on 4/2/2024
Muon Space

51-200 employees

Deploys custom space sensors for data insights
Company Overview
Muon Space stands out in the industry through its unique approach of deploying custom space sensors, tailored to the specific needs of their clients, thereby providing a competitive advantage in obtaining precise and actionable data. The company's culture emphasizes close collaboration between their team of scientists, operations, and data teams, ensuring a seamless and efficient process from understanding client needs to data implementation. As a leader in space-based sensing solutions, Muon Space is redefining our understanding of the planet, demonstrating technical prowess and industry leadership.
Energy

Company Stage

Series A

Total Funding

$35M

Founded

2021

Headquarters

Mountain View, California

Growth & Insights
Headcount

6 month growth

4%

1 year growth

38%

2 year growth

148%
Locations
Mountain View, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Microsoft Azure
Python
AWS
Data Analysis
Google Cloud Platform
CategoriesNew
Software Engineering
Requirements
  • B.S., M.S., or Ph.D. in computer science or related field, or equivalent experience
  • 5+ years experience as a software engineer in a team environment
  • Strong programming experience in Python, with knowledge of industry-standard data formats and schemas (ProtoBuf, YAML, JSON, etc)
  • Experience with cloud-native software development in at least one major cloud provider (AWS, GCP, Azure) using containers
  • Excellent communication and presentation skills
  • Excited to work in a fast-paced environment with new opportunities each week
Responsibilities
  • Participate in designing our cloud architecture
  • Manage the cloud infrastructure
  • Build a world class Mission Control in the cloud
  • Build the spacecraft-to-cloud data integration
  • Build the APIs and tooling to integrate our cloud with remote antenna ground station networks
  • Collaborate with Data Engineers to define, manage, and maintain our data processing environments
  • Integrate physical test hardware in our lab with our cloud systems
  • Architect systems to achieve low latency and fault tolerance
  • Deploy infrastructure and tools to workstations, on-premises data centers, and cloud environments