Remote Geospatial ML Solutions Engineer

Summary

The job is for a Geospatial ML Solutions Engineer at Atlas AI in Europe. The role involves designing and implementing geospatial solutions, data management, AI/ML, cloud deployment, QA, documentation, collaboration with internal teams and external clients, and staying abreast of emerging technologies.

Requirements

• Master's degree in Computer Science, Machine Learning, Data Science, Software Engineering or a related field
• Three or more years of work experience as a Backend Software Engineer deploying Data Science and/or Machine Learning workflows and pipelines in the cloud as serverless applications (e.g. GCP Cloud Run) or orchestrated workflows (e.g. Airflow, Argo)
• Demonstrable experience with Python, PyTorch, OpenCV, (Geo-) Pandas, scikit-learn, GDAL
• Demonstrable experience with deployment of image segmentation / object detection algorithms

Responsibilities

• Develop and implement geospatial solutions
• Data management and processing
• AI/ML: assemble application-specific training data sets, train and deploy proprietary and open AI/ML models, evaluate model performance and output quality, deploy at production scale
• Cloud: Architect scalable and serverless means of deploying your solutions that bring together assets within and across cloud platforms (e.g. GCP, AWS, Azure)
• QA: Develop thorough validation and Quality Assurance protocols to benchmark and assure robustness of solutions
• Create technical documentation: Develop clear and concise documentation for implemented solutions, including performance benchmarks, user guides, technical specifications, and training materials
• Collaborate with internal teams and external clients: Communicate technical details effectively, understand client needs, and provide expert guidance
• Stay abreast of emerging technologies: Continuously research and learn about new geospatial technologies and best practices

Preferred Qualifications

• Working knowledge of C++
• Deploying geospatial libraries at scale for user-facing applications
• Experience with building distributed computing infrastructure flexible for both on-demand and batch processing
• Developing enterprise SaaS products
• Developing on Google Cloud Platform

Benefits

• Competitive compensation
• Great benefits
• Casual and inclusive working environment
• Fully remote work with occasional in-person meet-ups in Europe & USA