At we are building a differentiated ML Ops and Data Ops platform powered by our own open source system along-with proprietary closed source components that are designed to elevate the experience of designing complicated ML and Data processing applications. We are constantly solving hardcore distributed systems problems that enable our customers applications to scale. Day to day you will be responsible for designing modern Golang based gRPC services, building core distributed scheduling systems on Kubernetes, managing terabytes of data in an efficient and secure manner and building simplified interfaces that delight our customers. We target ML Engineers, Data Engineers, Data Scientists and Systems Administrators. You will get to work on cutting edge problems and many of them will be open sourced and will provide you an opportunity to share your learnings with the broader open source community.


  • Large scale, multi-tenant, distributed Control plane for managing complicated ML and Data Processes
  • Performance engineering for Golang based applications
  • Building core algorithms that help distributed ML and data systems scale more easily
  • Work with the open source community and internal team members to deliver value across multiple organizations.


  • We are considering candidates with at least 2-3 years of experience building core distributed services and high performance systems engineering.
  • Bachelor’s Degree in Computer Science or related field, or equivalent experience
  • Excellent verbal and written communication skills to ensure seamless integration with a global team and the open-source community
  • Solid experience in Golang, python is a plus
  • Hands on knowledge of kubernetes and understanding core kubernetes principles is a plus
  • Understanding Data or ML systems is not required but desirable.
  • Ability to identify tasks which require automation and automate them
  • Expert knowledge of maintaining and debugging live software systems
  • Working in an open source environment is a plus, but not required.

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