Senior Machine Learning Engineer
Tasks
- Apply prompt engineering fine tuning and distillation
- Build and operate scalable ML pipelines on AWS
- Build predictive time series models with spatial context
- Collaborate on geospatial accuracy and coordinate reference system alignment
- Create generative multimodal models and natural language query systems
- Design train and productionize models for aerial image classification
- Develop change detection and structure change models
- Establish evaluation benchmarks and real world metrics
- Ground language in georeferenced pixels and semantic layers
- Integrate and optimize foundation models for aerial segmentation
- Perform object detection and 2D 3D segmentation
- Translate research into production ready model features
- Use SageMaker to train and host production endpoints
Perks/Benefits
Skills/Tech-stack
3D segmentation | AWS | AWS Step Functions | Aerial Imagery | Amazon S3 | Amazon SageMaker | Computer Science | Computer Vision | Coordinate reference systems | Deep learning | Diffusion Models | Fine Tuning | GDAL | Gaussian Splatting | Generative AI | Georeferencing | Geospatial Accuracy | Image Segmentation | Language Processing | Machine Learning | Model Distillation | Multimodal Learning | Natural Language | Natural Language Processing | Nerf | Object Detection | Photogrammetry | PostGIS | Prompt engineering | Python | RAG | Rasterio | Reference systems | Remote Sensing | Step Functions | Time Series
Education
Regions
Countries
States
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