Planet's Built Environment applied machine learning team needs to deliver advanced geospatial products, including change detection, object detection, and generative AI capabilities, primarily for Defense and Intelligence applications. This involves implementing novel machine learning methods, ensuring rigorous testing and validation, and deploying solutions at scale to derive insights from satellite and aerial data.
Requirements
- Deep familiarity with time series methods, computer vision, and embeddings; able 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
- Practical knowledge of remote sensing, satellite imagery, or related geospatial domains
Responsibilities
- End-to-end model development & maintenance: Develop new algorithms or methods, implement and test them rigorously, and integrate them into production pipelines. Contribute to their ongoing maintenance and iteratively improve them.
- Advancing geospatial analytics: Innovate on computer vision, time series, and other ML techniques to uncover new insights from satellite and aerial data.
- Cross-functional collaboration: Partner with product managers, data scientists, and engineers to define requirements, validate model outputs, and refine algorithms in iterative cycles.
- Collaborating with adjacent ML and software engineering teams to ensure seamless integration of ML pre-processing and inference steps, defining best practices for efficient deployment and maintenance of geospatial models.
Other
- This is a full-time, hybrid role which will require you to work from our D.C. office (Arlington, VA) 3 days per week.
- Ability to obtain and maintain US Security Clearance
- Excellent communication skills, capable of explaining technical topics to diverse audiences.
- Bachelor’s degree in a STEM or analytics-focused field or equivalent work experience.
