Job Description
The role involves developing and optimizing AI and machine learning models for geospatial imagery analysis, utilizing vision-language models and other advanced AI techniques to extract insights from satellite data and support remote sensing applications.
Key Responsibilities
- Develop and optimize multimodal language models and embedding search pipelines for geospatial imagery analysis
- Fine-tune foundation models such as CLIP, MAEs, and ViTs for Earth observation tasks
- Design and execute machine learning workflows for geospatial data analysis
- Collaborate with research scientists and engineers to create innovative remote sensing models
- Automate preprocessing and labeling of geospatial data for AI applications
- Evaluate and improve algorithms for feature detection and classification in satellite imagery
- Publish research findings in relevant conferences and journals
Requirements
- Advanced degree in Computer Science, Artificial Intelligence, Remote Sensing, or similar field.
- 12 years of expertise or demonstrably equivalent experience in 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, large language models (LLMs), and agents, e.g., Google ADK, Model Context Protocol, CrewAI, Langchain, etc.
- Extensive experience in developing and deploying AI/ML models, with a focus on geospatial applications and foundation models, embeddings, and frontier vision-language models (VLLMs).
- Excellent understanding of generative AI techniques, including LLMs and embeddings.
- Proficiency in Python and deep learning frameworks, and experience with high-performance distributed computing and IO frameworks using the Python ecosystem, e.g., xarrays, dask, numpy, BigQuery.
- Expertise with computer vision and natural language processing techniques, and familiarity with joint multimodal embeddings generators like CLIP and its variants, as well as the operation and use of multi-model vision-language models (MMVLMs).
- Familiarity with multi-dimensional geometry, statistics, linear algebra, optimization, and the internals of standard deep learning architectures.
- Fluency in full stack development and effective GUI implementation for web applications that rely on back-end scientific and AI systems.
- Knowledge of geospatial data formats and analysis tools such as GDAL, GeoPandas, Rasterio.
- Excellent problem-solving skills and the ability to work in a dynamic research environment.
- Experience with cloud computing platforms such as AWS, GCP, or Azure, and big data workflows.
- Excellent communication and collaboration skills.
- Ability to access export-controlled information without additional export licensing, as required by EAR ITAR regulations.
Benefits & Perks
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
Discretionary short-term and long-term incentives bonus and equity
Salary range depending on location (e.g., New York City: $217,900 - $272,400, San Francisco: $231,500 - $289,400, US National: $203,300 - $254,100)
Ready to Apply?
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