Intern, Mission Optimization Engineer at Planet in San Francisco, CA

Summary: Planet Labs is a company that designs, builds, and operates the largest constellation of imaging satellites in history. They are seeking a Mission Optimization Engineer Intern to support the productivity of their Earth Observation satellite constellation by developing software solutions and optimizing fleet operations. Responsibilities: - Develop and maintain real-time, mission-critical software solutions for satellite operations - Write scripts to aggregate satellite data and generate system monitoring metrics - Analyze data to identify issues and inefficiencies in the full stack of services and propose solutions to improve productivity - Identify and drive improvements to fleet capacity and productivity through process enhancements Required Qualifications: - Currently enrolled in a BSc in engineering or computer science - Proficiency in software development, particularly in Python or equivalent languages - Data-driven mindset with experience in statistical analysis - Proactive, self-starter approach to engineering and problem-solving - Effective interpersonal and collaboration skills within a technical team Preferred Qualifications: - Experience with agile software development - Experience with DevOps tools and practices (e.g., Git, GitLab, Docker, Jenkins, Bash, Linux, CI/CD, Sentry, Datadog) - Familiarity with satellite engineering and/or the space environment and its challenges - Hands-on experience operating spacecraft or remote systems - Familiarity with automation and optimization frameworks - Contributions to open-source software projects Required Skills: Python, Software Development, Statistical Analysis, Agile Software Development, DevOps Tools, Git, GitLab, Docker, Jenkins, Bash, Linux, CI/CD, Sentry, Datadog, Satellite Engineering, Space Environment Knowledge, Automation Frameworks, Optimization Frameworks, Proactive Problem Solving Benefits: Commuter Benefits, Paid time off for holidays and company-wide days off, Internet reimbursement, Access to LinkedIn Learning