Associate Computer Vision Engineer

Welcome to Planet. We believe in using space to help life on Earth.

Planet designs, builds, and operates the largest constellation of imaging satellites in history. This constellation delivers an unprecedented dataset of empirical information via a revolutionary cloud-based platform to authoritative figures in commercial, environmental, and humanitarian sectors. We are both a space company and data company all rolled into one.

Customers and users across the globe use Planet's data to develop new technologies, drive revenue, power research, and solve our world’s toughest obstacles.

As we control every component of hardware design, manufacturing, data processing, and software engineering, our office is a truly inspiring mix of experts from a variety of domains.

We have a people-centric approach toward culture and community and we strive to iterate in a way that puts our team members first and prepares our company for growth. Join Planet and be a part of our mission to change the way people see the world.

Planet is a global company with employees working remotely world wide and joining us from offices in San Francisco, Washington DC, Germany, Austria, Slovenia, and The Netherlands.

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 Associate Computer Vision Engineer to work on the onboard compute and analytics effort on the next generation satellites.  You will work with a multidisciplinary team to design, prototype, test, and deploy geolocation algorithms and hardware/software solutions for processing data directly onboard satellites. This position offers the unique opportunity to work at the intersection of hardware, software, and machine learning to tackle challenging problems in Earth observation.

This is a part-time, temporary position based remotely in the United States.

Impact You'll Own:

• Combine neural-net based geolocation with GNSS, IMU & star tracker information to improve geolocation accuracy to sub-15 meters
• Develop SLAM-like techniques incorporating optical flow and constrained optimization for spatial consistency
• Calibrate and align main camera data with cloud camera data using modern transformer-based feature matching
• Curate datasets of image pairs for fine-tuning transformer-based models
• Develop and optimize neural nets for matching images at different scales and perspectives
• Investigate compression of key-point data into neural net weights for satellite storage and transmission
• Design and prototype embedded C++ software for satellite systems with a focus on real-time performance, robustness and power efficiency
• Conduct hardware in the loop (HIL) testing and validate algorithms on flight-equivalent hardware in simulated environments
• Perform rigorous testing and validation to ensure algorithms meet mission-specific accuracy and energy constraints
• Optimize system performance for cost, latency and onboard computation
• Document methodologies, results and findings in high-impact publications & contribute to the academic and applied geolocation research community

What You Bring:

• BS or MS/PhD in Electrical Engineering, Computer Science, Physics, or a related field.
• Proficiency in Computer Vision algorithms including SLAM, optical flow and geolocation techniques
• Proficiency in Python and C++.
• Proficiency with Deep Learning frameworks such as TensorFlow/Pytorch
• Familiarity with CUDA
• Understanding of satellite based sensors (eg: GPS, IMU, star-tracker) and their data fusion
• Experience developing and deploying algorithms in computationally constrained environments.
• Experience with hardware/software integration and system architecture.

What Makes You Stand Out: 

• Experience with satellite imaging systems and geolocation on earth observation data sets
• Background in constrained optimization
• Low-level programming experience in CUDA/OpenCL
• Excellent communication and analytical skills
• Self-motivated and a great teammate

Application Deadline:

January 31, 2025 by 11:45pm PT.

#LI-REMOTE

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