This Senior Backend Engineer, Applied ML position for our new applied machine learning team is 100% remote.

About the team: Applied machine learning

With our recent acquisition of UnReview, we have launched our new applied-machine learning team, which will bring workflow automation, powered by machine learning, to identify the correct code reviewer. We will expand to other use cases in the future. 

The current priorities for the team are to create a Proof of Concept (PoC) for this first code review use case, then to productionize and integrate the PoC into the product. This team will also help GitLab integrate machine learning capabilities across our single devops platform.  

This team primarily writes code in Python and Ruby on Rails.

GitLab Culture

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.

What you'll do in this role

• Contribute to the overall direction of the team
• Play a key role in the design, implementation and integration of product features.
• Solve technical problems of high scope and complexity.
• Test, deploy, maintain and improve ML models/infrastructure and software that uses these models
• Partner on changes with other teams including create, growth.
• Help to define and improve our internal standards for style, maintainability, and best practices for a high-scale web environment. .
• Confidently ship moderately sized features and improvements with minimal guidance and support from other team members.
• Collaborate with the team on larger projects.
• Improve the engineering projects at GitLab via maintainer trainee program at your own comfortable pace, while striving to become a project maintainer.

You should apply if you bring:

• Significant professional experience in Python.
• Experience in working with pytorch , TF and other frameworks or interest in learning various ML frameworks.
• High interest in writing software for ML driven recommendation engines (experience with this, however is a nice-to-have).
• Experience in scaling ML models.
• 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.
• Comfort working in a highly agile, intensely iterative software development process.
• Demonstrated ability to onboard and integrate with an organization long-term.
• Positive and solution-oriented mindset.
• Effective communication skills: Regularly achieve consensus with peers, and clear status updates.
• An inclination towards communication, inclusion, and visibility.
• Experience owning a project from concept to production, including proposal, discussion, and execution.
• Self-motivated and self-managing, with strong organizational skills.
• Demonstrated ability to work closely with other parts of the organization.
• Share our values, and work in accordance with those values.
• Comfort working in earlier stages of product development.
• A genuine passion for learning.

Nice to have attributes:

• Research or Industry experience in ML Engineering and Infrastructure.
• Experience with Kubernetes and MLFlow or Kubeflow or similar MLOps stack
• Experience with cloud architecture optimization (GDF, PubSub, GCP).
• Experience in Continuous training of models

Also, we know it’s tough, but please try to avoid the ​​confidence gap ​. You don’t have to match all the listed requirements exactly to be considered for this role.

Hiring Process

Our hiring process for this position typically follows four stages. The details of this process and our leveling structure can be found on our job family page.

For Colorado residents: The base salary range for this role’s listed level is currently $89,600 - $157,400  for Colorado residents only. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, and alignment with market data. See more information on our benefits and equity. Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. Disclosure as required by the Colorado Equal Pay for Equal Work Act, C.R.S. § 8-5-101 et seq.