Senior Machine Learning Engineer

Planet•Arlington, TX

11d•Hybrid

About The Position

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.

Requirements

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

Nice To Haves

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

Responsibilities

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.