Fullstack Engineering Manager, Applied ML
GitLab (View all Jobs)
1. A series of video calls 2. Coding exercise involving working on a Merge Request that is like a real work task
Programming Languages Mentioned
The GitLab DevSecOps platform empowers 100,000+ organizations to deliver software faster and more efficiently. We are one of the world’s largest all-remote companies with 2,000+ team members and values that foster a culture where people embrace the belief that everyone can contribute. Learn more about Life at GitLab.
The Applied ML group is focused on how to extend GitLab functionality to provide additional value by leveraging ML/AI. This group will build on existing successful GitLab categories and features to make them smarter, easier to use, and more intelligent. You can find more information about our most recent release, Suggested Reviewers, in GitLab 15.4.
The Fullstack Engineering Manager specializes in Engineering Management as a manager of people. Engineering Managers at GitLab see their team as their product. While they are technically credible and know the details of what engineers work on, their time is spent safeguarding their team's health, hiring a world-class team, and putting them in the best position to succeed. They own the delivery of product commitments and are always looking to improve productivity. They must also coordinate across departments to accomplish collaborative goals.
What you’ll do in this role:
- Manage and grow a team of backend, frontend, and machine learning engineers
- Collaborate with the Product Manager to help inform planning and author project plans for epics, and influence the overall direction of Applied ML
- Run agile project management processes. We work iteratively and release monthly.
- Provide guidance and coaching to team members on technical contributions, product architecture, and other areas.
- In addition to the Product Manager, work with the rest of the team (e.g. Engineers, Software Engineers in Test) to ensure the team direction is clear, and the team is delivering value aligned with business needs.
- Maintain empathy for the team by keeping awareness of engineering processes and practices. Examples may include:
- evaluating individual workflow during one on ones
- ensuring production readiness reviews are being conducted
- collaborating with internal stakeholders throughout the department, as the single point of contact for any internal Applied ML requests
- Actively seek and hire globally-distributed talent
- Contribute to the sense of psychological safety in your team
- Foster technical decision making on the team, but make final decisions when necessary
- Draft quarterly OKRs and Engineering KPIs
What you’ll need to apply:
- Exquisite brokering skills: regularly achieve consensus amongst departments
- Demonstrated experience as a People Manager for backend teams with a servant leadership mindset
- A track record of supporting engineering teams in building scalable and impactful ML solutions
- Excellent written and verbal communication skills
- You share our values, and work in accordance with those values
You’ll stand out if you bring:
- Experience with the GitLab product as a user or contributor
- Working knowledge of modern frontend frameworks such as React or Vue.js
- Product company or startup experience
- Computer Science education or equivalent experience
- Passionate about open source and developer tools
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 and compensation:
Our hiring process for the Applied ML team typically follows five stages including an initial call with our Technical Recruitment team. Candidates will have access to the compensation calculator after the initial screen conversation with a member of our recruiting team. Additional details about our process can be found on our hiring page.
What it’s like to work here at GitLab:
The culture here at GitLab is something we’re incredibly proud of. You’ll spend your time collaborating with kind, talented, and motivated colleagues from across the globe.
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 flexible paid-time-off policy, where we don’t count the number of days you take off annually.
You can work incredibly flexible hours, enabled by our asynchronous approach to communication. We’ll also help you set up your home office environment, pay for your membership to a co-working space and contribute to the travel costs associated with meeting other GitLab employees across the world.
Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process.
GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know during the recruiting process.
Please mention No Whiteboard if you apply!
I'm a one-man team looking to improve tech interviews, and could use any support! 😄