Staff Software Engineer, Compute

Posted 20 Hours Ago
Easy Apply
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Hiring Remotely in US
Remote
204K-240K Annually
7+ Years Experience
Artificial Intelligence • Machine Learning
Unleash Enterprise AI, one innovation at a time.
The Role
Contribute to architectural initiatives, prioritize and plan for improvements, drive standards for service architecture, analyze scale requirements, and collaborate with engineering teams at Domino Data Lab as a Staff Software Engineer in the Compute team.
Summary Generated by Built In

Domino Data Lab powers model-driven businesses with its leading Enterprise AI platform trusted by over 20% of the Fortune 100. Domino accelerates the development and deployment of data science work while increasing collaboration and governance. With Domino, enterprises worldwide can develop better medicines, grow more productive crops, build better cars, and much more. Founded in 2013, Domino is backed by Coatue Management, Great Hill Partners, Highland Capital, Sequoia Capital and other leading investors. For more information, visit www.domino.ai

The Compute team at Domino is enabling customers to perform data-science activities across a range of hybrid/on-prem/cloud architectures.  The team drives Domino’s Nexus offering and continues to establish standards within Domino’s Platform Engineering organization for improved workload execution, security and scalability.

In your first year, you will 

  • Contribute to current Nexus architecture initiatives and milestones
  • Work with the engineering teams to review, prioritize and plan for architectural improvements outside of Nexus.
  • Drive standards for the “operator pattern” and service architecture to ensure other engineering teams are considering and implementing maintainable patterns.
  • Work with Scale team to analyze and provide recommendations based on scale requirements of the Domino platform

  • 8+ years previously in a software engineering individual contributor role
  • Strong knowledge of one or more programming languages, such as Scala, Java, Kotlin, Go, C/C++, C#
  • Experience in design and development of large scale distributed systems
  • Strong understanding of data structures, algorithms, and software design principles
  • Excellent problem-solving and communication skills

  • We value a growth mindset. High-performing creative individuals who dig into problems and see the opportunities for success
  • We believe in individuals who seek truth and speak the truth and can be their whole selves at work
  • We value all of you that believe improving is always possible At Domino Everything is a work in progress – we can do better at everything
  • We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company
  • We strongly believe in the value of growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply

#LI-Remote

Compensation Range

$204,000$240,000 USD

Top Skills

C
C++
Go
Java
Kotlin
Scala
The Company
San Francisco, CA
340 Employees
Hybrid Workplace
Year Founded: 2013

What We Do

Domino Data Lab powers model-driven businesses with its leading Enterprise AI platform trusted by over 20% of the Fortune 100. Domino accelerates the development and deployment of data science work while increasing collaboration and governance. With Domino, enterprises worldwide can develop better medicines, grow more productive crops, build better cars, and much more. Founded in 2013, Domino is backed by Coatue Management, Great Hill Partners, Highland Capital, Sequoia Capital and other leading investors. For more information, visit www.domino.ai

Why Work With Us

We’re looking for sharp, scrappy people who crave a high degree of ownership, are laser-focused on personal growth, and can stick the landing between high standards and low ego. In our fast-paced environment, you’ll find all the white space and opportunity you need to thrive.

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Domino Data Lab Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Typical time on-site: Flexible
San Francisco, CA

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