GitLab is an open core software company that develops the most comprehensive AI-powered DevSecOps Platform, used by more than 100,000 organizations. Our mission is to enable everyone to contribute to and co-create the software that powers our world. When everyone can contribute, consumers become contributors, significantly accelerating the rate of human progress. This mission is integral to our culture, influencing how we hire, build products, and lead our industry. We make this possible at GitLab by running our operations on our product and staying aligned with our values. Learn more about Life at GitLab.
Thanks to products like Duo Enterprise, and Duo Workflow, customers get the benefit of AI at every stage of the SDLC. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier. All team members are encouraged and expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact across our global organisation.

BONUS QUALIFICATIONS

• Have contributed a Merge Request to GitLab
• Have contributed to ML open source projects

AN OVERVIEW OF THIS ROLE

The Custom Models team is responsible for Duo Self-Hosted, a key component in GitLab AI that allows customers to run GitLab Duo features on completely private environments, connecting GitLab to their own AI models. They work collaboratively with numerous teams to ensure a complete lifecycle of assessing models, evaluating features, implementing controls for customization and guaranteeing a smooth experience for our largest customers.
Why us? This isn’t just a job; it’s your chance to shape the future of AI at GitLab. Your expertise in backend development will be critical to your success. Ready to dive into the future of AI at GitLab? Apply now! We’re excited to meet potential candidates like you and welcome a new star to our team. Let’s shape the future together!

WHAT YOU’LL DO

• Develop evaluation techniques to assist feature teams on guaranteeing the quality of their features on new models.
• Evolve the Evaluation Runner, our internal tool for scaling AI Feature evaluation
• Keep up with the industry to explore brand new models.
• Deploy and manage LLMs internally for evaluation and development.
• Collaborate with product managers, engineers, and other stakeholders as a machine learning specialist, guiding them on effective implementation of AI features.
• Advocate for improvements to product quality, security, and performance.
• Solve technical problems of moderate scope and complexity.
• Craft code that meets our internal standards for style, maintainability, and best practices for a high-scale machine-learning environment. Maintain and advocate for these standards through code review.
• Confidently ship small features and improvements with minimal guidance and support from other team members. Collaborate with the team on larger projects.
• Participate as a reviewer or project maintainer in one or more engineering projects.