Senior Machine Learning Engineer

📋 Job Overview

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 Planet

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.

🎯 The Role

This is a full-time, hybrid role which will require you to work from our Arlington, VA office 3 days per week.

✅ Key Responsibilities

• Optimize model performance to execute high-throughput inference at continental and global scales.
• Innovate computer vision, time series, and embeddings-based techniques to uncover new insights from satellite data.
• Collaborate with product managers, data scientists, and engineers to define requirements and iterate on algorithm designs.
• Integrate ML pre-processing and inference pipelines seamlessly with adjacent software engineering platforms.
• Establish best-in-class testing, validation, and monitoring frameworks for continuous model reliability.

📌 Required Qualifications

• 10+ years of relevant experience of which 6+ years of experience is in machine learning.
• Ability to conduct a rigorous evaluation of results and internal communication of algorithm failure modes.
• Expertise with data science, time series methods, computer vision, and embeddings.
• Ability to implement, train, and optimize neural networks.
• Experience wrangling large datasets, ideally with geospatial libraries, combined with frameworks like PyTorch/TF for model development and training.
• Ability to experiment with model architectures, and derive data-driven insights to iteratively improve performance and accuracy.
• Experience writing clean, modular Python code and applying software development best practices (Git, testing, CI/CD).
• Experience deploying models (via Docker, Kubernetes, or similar) with an understanding of best practices for monitoring and maintaining them at scale.
• AWS or GCP experience
• Excellent communication skills, capable of explaining technical topics to diverse audiences.
• Graduate degree in a STEM or analytics-focused field or equivalent work experience.
• Located in the Washington, DC metro or ability to work and commute to Arlington, VA 3x/week
• Ability to obtain and maintain US Security Clearance

⭐ Desirable Experience

• Practical knowledge of remote sensing, satellite imagery, or related geospatial domains
• Knowledge of coordinate reference systems, geometry manipulations, and common data formats (GeoTIFF, GeoJSON, etc).
• Hands-on experience building geospatial or sensor-driven data products from scratch
• Familiarity with techniques like model compression, GPU optimizations, or distributed training pipelines

🎁 Benefits

• 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
• 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

🛂 Visa & Eligibility

• 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.
• Ability to obtain and maintain US Security Clearance