Senior Machine Learning Engineer

About the Role:

Planet’s Analytics Team for Global Monitoring focuses on novel geospatial and time series analytics for customers requiring robust change detection, object detection, and generative AI capabilities. As a Senior Machine Learning Engineer, you will drive hands-on engineering and modeling for Defense and Intelligence applications. You’ll implement novel embeddings-based change detection and advanced computer vision techniques. In this role, you will ensure best-in-class testing and deploy solutions to run at continental and global scales. You’ll collaborate closely with data scientists and software engineers to drive innovation in remote sensing and large-scale geospatial analytics. Ideal candidates bring a creative mindset and passion for solving complex geospatial challenges.

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

Impact You'll Own:

• Spearhead the development of novel algorithms and machine learning models tailored for Defense and Intelligence applications.
• 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.

What You Bring:

• 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

What Makes You Stand Out:

• 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

Application Deadline:

11:45pm PT on the date stated below. Applications are reviewed on a rolling basis. This posting may be removed earlier than projected if a suitable pool of applications has been received. For this reason, we recommend applying as soon as you are able to.

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
• 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.

US National Salary Range 160600 - 200800 USD