Machine Learning Engineer(Remote)
Project Detail
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.
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