Atlas AI is hiring a
Senior ML Tooling Software Engineer

Summary

The job is for a Senior/Lead ML Tooling Software Engineer at Atlas AI. The role involves designing, developing, deploying, and supporting cloud-scale training services for GeoSpatial Machine Learning models. The employee will work with various teams to improve the product roadmap and engineering standards.

Requirements

• Three or more years of recent work experience as a practicing Data Scientist or Machine Learning Engineer using PyTorch, sklearn and lightgbm
• Two or more years of recent work experience as a practicing Backend Software Engineer using Python, GDAL and other GeoSpatial tools deployed in the cloud as serverless applications (e.g. GCP Cloud Run) or orchestrated workflows (e.g. Airflow, Argo)
• At least three or more years of recent work experience building around Earth Observation use-cases
• Technical ownership of key areas of a Product, such as one or two critical services

Responsibilities

• Own the design, development, deployment, and support of our cloud-scale training services for GeoSpatial Machine Learning models
• Be the Subject Matter Expert ensuring that the Software Engineering team builds and delivers solutions that ‘just work’ for how DS and MLE approach GeoSpatial problems in the real world
• Engage internal collaborators and our end-use partners and customers to understand needs, plan solutions and lead development of deliverables
• Close the feedback loop with Solutions, Engineering and Innovation teams to deliver customer experience and market insights
• Architect and develop serverless solutions that marry products within and across cloud platforms (e.g. GCP, AWS, Azure) that address customers’ needs
• Lead client-oriented API design and development
• Work with designers, product managers, and your fellow engineers to build APIs to support key functionality and use cases
• Actively participate to improve engineering standards, tooling, and processes

Preferred Qualifications

Demonstrable experience with building distributed computing infrastructure flexible for both on-demand and batch processing

Benefits

• Competitive compensation
• Great benefits
• Casual and inclusive working environment