At Numbers Station, we’re using the latest revolution in artificial intelligence to automate enterprise data tasks. In particular, we use foundation models (e.g. GPT-3) to automate challenging enterprise data tasks such as data cleaning and extraction from richly formatted sources. Ultimately this leads to higher quality, better return on investment, and new possibilities for enterprises adopting our revolutionary technology. Numbers Station is born out of years of research at Stanford University and our technology already powers assistants and search engines at top tech companies. Numbers Station is bringing this technology to the broader enterprise. 

Excited to join a young startup redefining how enterprises use AI? Apply to be a cloud infrastructure engineer on the Numbers Station team. As a Cloud Infrastructure Engineer you’ll lead the successful design and implementation of the Numbers Station Platform for our hosted cloud environments. You will be responsible for building and operationalizing our multi-cloud enterprise machine learning platform, consisting of a multi-tenant control plane with isolated data planes running within each customer VPC, a serverless compute abstraction, and cloud-native tech stack built on top of Kubernetes. This is a new role to Numbers Station and you will be its founding member responsible for shaping the approach we apply to future customer engagements. You’ll work closely with our internal engineering teams to improve the design, architecture and implementation of Numbers Station. This is a phenomenal opportunity to join our team and drive our strategy for the future.

Main Responsibilities

  • Design, prototype, and refine infrastructure for operating Numbers Station’s machine learning pipeline at scale within cloud environments
  • Lead the full lifecycle of a cloud implementation including the implementation and testing of the Numbers Station Platform
  • Work closely with our Product Management, Product Engineering, and Support teams to resolve issues that occur during the implementation
  • In some situations, provide training and limited post-implementation support
  • Be a Subject Matter Expert (SME) on the Numbers Station position, architecture, and product
  • Contribute to the Numbers Station user documentation, including but not limited to design, testing, delivery and training

Minimum Qualifications

  • 3+ years experience in a Infrastructure Engineering or similar role
  • Previous experience with cloud infrastructure providers such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform
  • Hands-on experience with common container and container orchestration solutions, e.g., Docker Enterprise,Kubernetes, HashiCorp stack
  • Comfortable working in Linux environments
  • Excellent problem solving, critical thinking, and interpersonal skills
  • Experience supporting customer engagements as a Solution Architect, DevOps or System Administrator for commercial SaaS solutions
  • B.S. degree in Computer Science, Engineering, or comparable degree/experience

Preferred Qualifications

  • Experience operating Kubernetes orchestration tools in a production setting
  • Proficiency in Python, especially when setting up automation and system monitoring
  • Exposure to authentication protocols like LDAP, SAML and OAuth2
  • Knowledge of industry standard technologies in the Data Science and Machine Learning space
  • Expertise with Terraform
  • Experience implementing software products or solutions to large enterprise companies
  • Comfortable working in a fast-paced, small-team environment where you’ll wear many hats

Numbers Station is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.

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