Cloud Services Engineer

ABOUT US brings state-of-the-art artificial intelligence to the edge. XNOR’s platform allows companies to run complex deep learning algorithms, formerly restricted to the cloud, locally on a range of devices including mobile phones, drones, and wearables. This new, highly scalable approach ensures complete privacy of data, eliminates the need for connectivity, and significantly reduces memory load and power demands, all without compromising accuracy or performance. XNOR is a venture-funded startup, founded on award-winning research conducted at the University of Washington and the Allen Institute for Artificial Intelligence. XNOR’s industry-leading technology is used by global corporations in aerospace, automotive, retail, photography, and consumer electronics.


As a team, we are working to define and solve the hardest problems in computer vision and AI. Our roots are in research, which means at our core, we value learning, intellectual curiosity, and self-starters. We are proud to maintain a high engineering bar as our team scales, and it’s clear to anyone that works with our code that our development process favors quality. The software we write is portable across many platforms with little to no change. We stand by the importance of sticking with hard problems and working to solve them semi-autonomously at first. As a team, we are always willing to help but look for people who are committed to figuring things out.  

As a startup, we never shoehorn people into fixed roles. At XNOR.AI, there is no hard line between machine learning and engineering. We expect our engineers to understand how deep learning works and our research scientists to be able to code. This shared understanding results in deep collaborations that enable our team to rapidly develop novel models and optimized infrastructures of the highest production quality


As a Cloud Services Engineer you will be responsible for creating the systems and infrastructure that power Xnor’s large-scale Deep Learning infrastructure, SDK and web platform for ML model generation and tuning, and designing complex multi-tenant data and training workflows.

Our ideal team member is enthusiastic in trying new things, and is willing to iterate on ideas. We value team members who can quickly prototype, iterating all the way to high-quality implementations.


  • Lead tech selection and system design for Xnor’s cloud services and model training infrastructure
  • Design and build web platform and digital marketplace for selecting, tuning, and management of ML models for a broad developer community
  • Set engineering standards and operations procedures that are scalable and maintainable as our team grows

Minimum Qualifications

  • Expertise with full-stack web development
  • Experience with Google Cloud, AWS, or similar cloud platforms
  • Experience building technology using modern DevOps practices
  • Proficient writing code in Python or Java
  • Experience designing and implementing RESTful APIs
  • Experience with data intensive applications and workflow development
  • Experience designing and building services based operational requirements, incorporating metrics and monitoring for visibility

Preferred Qualifications

  • Experience with modern data-tier systems like DynamoDB, Bigtable, etc.
  • Experience working with or building Machine Learning technologies
  • Experience building and deploying services using Docker, Kubernetes (or similar technologies)
  • Experience with web application frameworks such as React, Angular, etc.
  • Experience working with designers and design teams to create user-facing web experiences

Benefits and Perks

  • Competitive salary and stock option packages
  • Comprehensive health care plan
  • 401K
  • Unlimited PTO
  • Gym membership
  • Conference travel
  • Culture of learning
  • Healthy lunch and snacks
  • Regular team activities
  • Standing Desks
  • Waterfront views
  • Support for obtaining a visa through its immigration attorney, and pays the necessary expenses is proud to be an Equal Opportunity Employer.

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