Sr. Machine Learning Infrastructure Engineer




Our mission is to understand what we’re doing on, and to, Earth. We do this through our cloud-based SaaS platform, Orbital Insight GO, pulling in multiple sources of raw data from the world’s sensors – including millions of daily satellite images and connected device pings – combined with proprietary AI to analyze economic, social, and environmental trends at scale. By making the Earth “searchable” our customers have been able to illuminate supply chains, track global commodities, monitor illegal deforestation, and further national security. We are building the best AI team in the world to innovate, implement, deploy, and support these capabilities.

We are data detectives and our job is difficult because although we have Big Data, we exist in a persistent state of spatio-temporal data starvation. The work is fast-paced, highly iterative, and continuously trading off between what works and what’s best. Along with our team of data scientists, you’ll work with product managers, sales, and software engineers to build data-driven products and solutions. If you enjoy working with data to build products and solve hard problems in creative ways, you will fit right in.

As a part of the Model Engineering team, you will work within a cross-functional team that is responsible for the full algorithm development process, all the way from human annotation to integration with the platform. Your role as a Sr. Machine Learning Infrastructure engineer means that you will be the lead software engineer for our Computer Vision sub-team and will be responsible for owning infrastructure for experiment tracking, model training/inference, dataset version control, and imagery annotation campaign creation and data extraction. You will work closely with our Platform and Product Engineering teams, as well as our Content team, to guide high-level engineering of the platform.


  • Develop workflows and pipelines for faster and more efficient imagery annotation, model training, model deployment, and continual monitoring of computer vision algorithms
  • Design a scalable architecture to support our multi-source, geospatial analytics platform
  • Develop and deploy microservices/REST APIs for machine learning model inference using Kubernetes
  • Mentor other members on your team with code reviews, design discussions, and new technologies
  • Collaborate with engineers on our Platform and Product Engineering teams
  • Qualifications

  • US Citizenship Required (Clearance Eligible)
  • Bachelors or Masters degree in a STEM field (e.g., computer science, machine learning, statistics, physics, engineering)
  • 3+ years industry experience in related role and 5+ years experience with Python (or similar language)
  • Experience in building machine learning infrastructure, including model hosting, serving, and/or inference pipelines
  • Familiarity with evolving ML ecosystems (e.g. kubeflow, mlflow, etc.) and with related infrastructure integration challenges
  • Proven ability to build scalable software operating on large datasets and with a high degree of task parallelism in Python (or similar language)
  • Strong analytical and problem solving skills, including software debugging, and familiarity with the challenges of developing computer vision algorithms
  • Experience in deep learning and related toolkits (e.g., Tensorflow, Pytorch) is a major plus
  • Working experience with cloud computing platforms like AWS
  • Additional Information

    About Orbital

    Orbital Insight is a fast growing provider of geospatial data and geo­-analytic services to commercial, nonprofit and public sector clients across the globe. Leveraging advancements in computer vision and cloud computing, Orbital Insight is turning millions of images into a big picture understanding of the world that is quantitatively grounded in observation, creating unprecedented transparency, and empowering global decision makers with new sources of objective, quantified socio­-economic insights.

    We are backed by marquee investors such as Google Ventures, Sequoia Capital, In­-Q­- Tel and Bloomberg Beta, Orbital Insight is rapidly expanding its commercial and public sector capabilities. Come join us if you are unafraid to try new approaches and relentlessly seek to push the state of the art, taking projects all the way from prototype to production-ready.
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