Senior Applied AI Engineer

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 the Role:

We are seeking a talented Senior Artificial Intelligence (AI) engineer to join our AI Research team and contribute to our vision of creating a “Queryable Earth”. In this role, you will work with cutting-edge vision-language models (VLMs) and contrastive vision-language embedding models to extract valuable insights from our extensive archive of geospatial imagery. This is a fantastic opportunity to contribute to accelerate the shift in how geospatial data is consumed by end users. You will work with highly skilled Planeteers working on multi-disciplinary fields  including satellites, space operations, image processing, data pipeline and analytics teams and work to co-develop AI/ML solutions for Planet’s geospatial imagery. Join us in revolutionizing how we understand and interact with our Planetary Dataset through the power of AI. 

This is a full-time, hybrid role which will require you to be in our San Francisco, HQ 3 days per week. 

Impact You'll Own:

• Develop and optimize multimodal LLM applications
• Create and optimize embeddings for large-scale satellite imagery datasets
• Design and execute machine learning workflows for geospatial analysis
• Contribute to the development of a "Queryable Earth" functionality using natural language queries
• Collaborate with research scientists and engineers to design innovative models for remote sensing applications
• Assist in automating the preprocessing and labeling geospatial data for AI tasks.
• Evaluate and improve algorithms for feature detection and classification in satellite imagery
• Potentially optimize and fine-tune novel VLMs tailored for Earth observation data

What You Bring:

• Advanced degree in Computer Science, Artificial Intelligence, Remote Sensing, or similar 
• 10+ years experience Computer Science, Artificial Intelligence, Remote Sensing, or a related field
• Experience with Remote Sensing, Satellite Image Analysis, and Geospatial Data
• Experience with rapid prototyping of AI Applications, especially search, LLMs, and agents including OpenAI agents SDK, Model Context Protocol, Langchain, etc.
• Extensive experience in developing and deploying AI/ML models, with a focus on geospatial applications and foundation models, embeddings, and frontier VLLMs
• Excellent understanding of generative AI techniques, including LLMs and embeddings.
• Proficient in Python and deep learning frameworks and high-performance distributed computing and IO frameworks using the python ecosystem, e.g. xarrays, dask, numpy, BigQuery, etc. 
• Expertise with computer vision and natural language processing techniques and familiarity with joint multimodal embeddings generators like CLIP and its more recent variants, as well as the operation and use of MMVLMS (multi-model vision-language models)
• ​​Familiarity with multi-dimensional geometry, statistics, linear algebra, optimization, and the internals of standard deep learning architectures
• Fluency in full stack-development development and effective GUI implementation for web applications which rely on back-end scientific and AI systems
• Knowledge of geospatial data formats and analysis tools (e.g., GDAL, GeoPandas, Rasterio)
• Excellent problem-solving skills and ability to work in a dynamic research environment
• Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and big data workflows 
• Excellent communication and collaboration skills