Planet's Analytics Team for Global Monitoring focuses on novel geospatial and time series analytics for customers who require robust analytics such as change detection, object detection, and emerging generative AI capabilities. This role is a blend of hands-on engineering and modeling focused on Defense and Intelligence applications.
Requirements
- 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.
Responsibilities
- Model development & optimization: Develop new algorithms or methods, implement and test them rigorously, and optimize them for high performance on global scales. 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 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
- 10+ years of relevant experience of which 6+ years of experience is in machine learning.
- AWS or GCP experience
- Excellent communication skills, capable of explaining technical topics to diverse audiences.
- 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
