Atlas AI is hiring a
Senior ML Tooling Software Engineer, Remote - Worldwide

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Senior ML Tooling Software Engineer

🏢 Atlas AI

💵 $170k-$200k
📍Worldwide

Summary

The job is for a Senior/Lead ML Tooling Software Engineer at Atlas AI, responsible for designing, developing, deploying, and supporting cloud-scale training services for GeoSpatial Machine Learning models. The role requires eligibility to work in the USA for a US company, and infrequent travel may be required.

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
  • Experience with applying Geospatial libraries and datasets at scale for user-facing applications
  • Developing enterprise PaaS and SaaS products
  • Working in early-stage startup environments
  • Developing on Google Cloud Platform

Benefits

  • Casual and inclusive working environment
  • Competitive compensation
  • Great benefits
  • Values-driven company, building products that are designed to improve lives and foster development across emerging markets
  • Salary range for candidates depending upon level of experience and location: $170,000 - $200,000

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