Edge Compute Machine Learning Engineer

About the Role:

Planet is working on the next generation small satellite bus that will host a high resolution optical imaging payload (Pelican) and a hyperspectral payload (Carbon Mapper). We are seeking an Edge Compute Machine Learning (ML) Engineer to develop edge compute solutions on the next generation satellites. . You will work with various teams to finalize the system requirements, develop functional specifications, develop CV models for various Earth Observation applications, benchmark the algorithms on the ground and ultimately deploy them in space for processing satellite imagery.  You will collaborate with electrical engineers, camera engineers, firmware engineers, data pipeline, and analytics engineers to build and iterate on the solution.

This is a full-time, hybrid role which will require you to be in our San Francisco HQ 3 days per week.

Impact You’ll Own:

• Develop onboard computer vision and machine learning models that enable real time segmentation, feature detection, and object recognition.  
• Develop pre-processing of raw imagery onboard the satellite to make them useable by the machine learning algorithms
• Collaborate with other space systems and software engineering teams to implement deep-learning-based classification systems on pre-processed imagery for identifying, characterizing, and classifying objects
• Explore and develop new methods for improving detection performance and improving the runtime of inference
• Work with internal customers to develop onboard processing and machine learning pipelines for various use cases and classification tasks
• Help to architect and develop the data pipeline and platform supporting onboard processing 
• Hardware/software co-development of edge computing solutions for Planet’s next generation spacecraft
• Own and drive performance metrics (e.g. latency, memory, bandwidth, power)

What You Bring:

• BS in EE/Aerospace/CS or equivalent experience
• 4+ years developing algorithms and solving problems pertaining to image processing, computer vision, object detection, machine learning
• Proven track record of algorithm development and solutions to solve real-world problems in computationally constrained environments
• Extensive experience programming in Python and/or C++ with computer vision libraries
• Understanding of version control (eg git) and CI tools
• Proficient in GPU-based computing frameworks (OpenCL/CUDA/TensorFlow)
• Understanding of embedded and high efficiency software architectures.
• Experience designing low latency, highly performant code
• Experience in hardware / software co-design

What Makes you Stand Out: 

• MS, PhD or similar advanced degree in relevant field
• Experience with machine learning on earth observation data sets
• Low level programming experience in CUDA/OpenCL
• Excellent communication and analytical skills
• Self-motivated and a great teammate

Application Deadline:

June 2, 2025 11:45pm PT

EAR/ITAR Requirements:

This position requires access to export-controlled information, and as such, employment (or hiring of a contractor) is contingent upon the candidate’s ability to access all applicable export-controlled information without additional export licensing being required by the Bureau of Industry and Security and/or the Directorate of Defense Trade Controls.

Benefits While Working at Planet:

These offerings are dependent on employment type and geographical location, based upon applicable law or company policy.

• Comprehensive Medical, Dental, and Vision plans
• Health Savings Account (HSA) with a company contribution
• Generous Paid Time Off in addition to holidays and company-wide days off 
• 16 Weeks of Paid Parental Leave
• Remote-friendly work environment 
• Wellness Program and Employee Assistance Program (EAP)
• Home Office Reimbursement
• Monthly Phone and Internet Reimbursement
• Tuition Reimbursement and access to LinkedIn Learning
• Equity
• Commuter Benefits (if local to an office)
• Volunteering Paid Time Off

Compensation:

The US base salary range for this full-time position at the commencement of employment is listed below.  Additionally, this role might be eligible for discretionary short-term and long-term incentives (bonus and equity). The final salary range is determined by job related experience, skills and location.  The range displays our typical hiring range for new hire salaries in US locations only.  Your recruiter can share more about the specific salary range for your preferred location during the hiring process.