Machine Learning Engineer, AI Powered: Custom Models

An overview of this role

The Custom Models team is responsible for allowing customers to deploy and customize the outputs of Generative AI models and fine-tune models for use within the GitLab product and beyond. They will work collaboratively with numerous teams to ensure a complete lifecycle of assessing models, fine-tuning models, evaluating models, storing models, deploying models, implementing models as underlying engines behind AI agents, and protecting these models through means of various hosting techniques.

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 improvements to models to generate new content using machine learning models in a secure, well-tested, and performant way.
• Work with highly complex data for feature development using machine learning models.
• Collaborate with product managers, engineers, and other stakeholders as a machine learning specialist.
• 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. 
• Participate in Tier 2 or Tier 3 weekday, weekend, and occasional night on-call rotations to assist with troubleshooting product operations, security operations, and urgent engineering issues.

What you’ll bring 

• A relevant Master’s degree and 2 or more years of experience in ML or PhD degree with a focus on Machine Learning or Data Science.
• Professional experience with Python
• 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
• Ability to thrive in a fully remote organization

Two of more of

• Professional experience with prompt engineering and Retrieval Augmented Generation (RAG)
• Experience building, training, and implementing deep learning models. 
• Experience with a deep learning framework such as PyTorch or TensorFlow
• Professional experience fine-tuning LLMs
• Design, construction or operation of MLOps infrastructure

Bonus qualifications

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

About the team

The Custom Models team is a new team formed with internal GitLab team members from around the globe. Engineers are primarily located across various European countries, with some distributions in Australia, New Zealand, America, and Canada. This team is growing, and there are currently 7 positions available.

The team works closely with these other teams within the organization:

• AI Framework

• MLOps

• Model Validation

• Duo Chat

How GitLab will support you

• Benefits to support your health, finances, and well-being
• All remote, asynchronous work environment
• Flexible Paid Time Off
• Team Member Resource Groups
• Equity Compensation & Employee Stock Purchase Plan
• Growth and development budget 
• Parental leave 
• Home office support

Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application.