Senior Software Engineer

Planet

21h•Remote

About The Position

Join Planet’s Software Engineering Team as a Full-stack AI/ML Engineer (P4) focused on pioneering geospatial analytics and computer vision solutions. We develop and deploy advanced machine-learning methods that transform massive, multi-modal imagery and sensor data (EO, MSI, SAR) into high-fidelity, actionable intelligence about global activity This is a full-time, remote position based in the United States. If located near an office, you are expected to work from that office 3 days per week.

Requirements

6+ years of relevant industry experience.
Bachelor’s degree in a related field.
Have the ability to obtain and maintainTS-SCI or DoD TS security clearance.
Expertise in Artificial Intelligence (AI) and Machine Learning (ML), including advanced algorithms and mathematical foundations.
Proficiency with Big Data and AI/ML at scale.
Experience with multi-modal data processing (EO, MSI, SAR), Computer Vision, and Perspective Geometry.
Full-stack capabilities, including front-end GUI, database management, and containerization (Docker).

Nice To Haves

Proficiency in Big Data and AI/ML at scale.
Ability to balance innovative and creative technological approaches with strong coding talent.
Expertise that can extend support beyond the Defense and Intelligence (D&I) sectors, aligning with Planet's strategic mission expansion.
Ability to operate with a high degree of autonomy and require minimal day-to-day oversight.

Responsibilities

Apply advanced expertise in AI/ML algorithms and mathematical foundations to process multi-modal data (EO, MSI, SAR), utilizing Computer Vision and Perspective Geometry to extract actionable intelligence at scale.
Take ownership of a core-product pipeline, driving its full-stack deployment, stability, and continuous technological improvement.
Operate with a high degree of autonomy to solve complex technical challenges with minimal guidance from technical leadership.
Execute full-stack capabilities—including front-end GUI, database management, and containerization (Docker)—balancing innovative technological approaches with strong coding talent for immediate operational deployment.
Work with existing team members by owning critical tasks, thereby increasing team bandwidth for broader scale initiatives and different focus areas.