Those in Single Engineer Groups (SEG) at GitLab work in the engineering department to initiate a planned or minimal maturity category into the GitLab project. The MLOps single engineer group has a focus on MLOps, which will be focused on enabling data teams to build, test, and deploy their machine learning models. This will be net new functionality within GitLab and will bridge the gap between DataOps teams, data scientists, and development teams to get data science workloads deployed to production.
Single engineer groups will work across the backend (Ruby on Rails and Go), and frontend (Vue.js) parts of our application. The work is weighted more strongly towards the backend, rather than frontend.
At GitLab, we believe in the power of a single engineer to accomplish amazing feats. Many open source projects started with a single engineer’s decision to build around a problem they personally experienced. For instance,Continuous Integration byDZ andGitLab Runner byKamil. In single engineer groups, we create room for this energy.
We can guarantee a higher rate of success by incubating ideas inside our larger organization and existing code base while limiting the negative aspects of friction that come from a larger organization. A few benefits of SEG include:
There are lots of decisions to be made, which happen more effectively in a single brain.
There is not enough code for multiple people to work on without running into merge conflicts.
Starting work earlier allows for more time for other people to contribute. We need to have a head start many years ahead of commercialization.
The culture here at GitLab is something we’re incredibly proud of. Some of the benefits you’ll be entitled to vary by the region or country you’re in. However, all GitLab team members are fully remote and receive a "no ask, must tell" paid-time-off policy, where we don’t count the number of days you take off annually -- instead, we focus on your results. You can work the hours you choose, enabled by our asynchronous approach to communication. You can also expect stock options and a competitive salary. Our compensation calculator will be shared with selected candidates before any interview.
Diversity, Inclusion, and Belonging (DIB) are fundamental to the success of GitLab. We want to infuse DIB in every way possible and in all that we do. We strive to create a transparent environment where all team members around the world feel that their voices are heard and welcomed. We also aim to be a place where people can show up as their full selves each day and contribute their best. With more than 100,000 organizations using GitLab, our goal is to have a team that is representative of our users.
Develop features and improvements to accomplish amazing things in a single engineer group. This person is a self-reliant team of one who does everything necessary to bring features from 0 to 1.
Understand the needs of those responsible for machine learning, and applies them to create awesome solutions to meet their needs.
Solve technical problems of high scope and complexity.
Craft code that meets our internal standards for style, maintainability, and best practices for a high-scale web environment.
Confidently ship and demo small features and improvements with minimal guidance and support from other team members.
Represent GitLab and its values in public communication around specific projects and community contributions.
A single engineer group at GitLab knows “just enough” product management, UX, quality, documentation, and project management principles to get the job done.
Must be passionate about and knowledgeable in machine learning
Must be excited about the ability to work independently or have prior success in a similar model working at senior engineer (or above)
Professional experience with Ruby and Rails or Go
Experience working with modern frontend frameworks (eg. React, Vue.js, Angular, CSS, semantic HTML)
Proficiency in the English language, both written and verbal, sufficient for success in a remote and largely asynchronous work environment
Demonstrated capacity to clearly and concisely communicate about complex technical, architectural, and/or organizational problems and propose thorough iterative solutions
Experience with performance and optimization problems and a demonstrated ability to both diagnose and prevent these problems