Job Description
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.
About the work
GitLab ModelOps aims to bring data science into GitLab both within existing and new features to make them smarter, more intelligent, and to empower GitLab customers to build and integrate data science workloads within GitLab. This stage also supports our FY24 Product Theme: GitLab for Data Science, and the GitLab company vision of developing an AllOps platform.
Your role will be to build and optimise our infrastructure and scale our LLM’s (large language models) while integrating them as microservices within Gitlab, and dropping the costs of Machine Learning. You will balance short and long-term efforts from an infrastructure perspective and work on scalability challenges. You will be the backbone of our ML efforts that solve the challenges of today and tomorrow.
Some examples:
- In GitLab version15.4 we released our Suggested Reviewers Open Beta
- In Gitlab version 15.3 we released Code Suggestion Closed Beta: a short blog
What you will do
- Play a key role in the design, implementation, and integration of product features;
- Solve technical infrastructure problems of high scope and complexity;
- Test, deploy, maintain, and improve ML infrastructure and software that uses these models;
- Help to define and improve our internal standards for style, maintainability, and best practices for a high-scale web environment;
- Collaborate with other ML engineers and advise on the MLOps architecture from an infrastructure perspective;
- Respond to feature availability incidents and provide support for service engineers with customer incidents.
What you will bring
- Significant professional experience in Python backend infrastructure and Pytorch.
- Experience in working on scalability and maintainability challenges
- Production experience with Terraform, Kubernetes, Docker, and preferably GCP or equivalent technologies.
- Experience with NVIDIA Triton backend and post-production monitoring of large language models ( >10GB)
- High interest in defining infrastructure for large-scale ML recommendation engines
- A genuine passion for learning as you will be solving the challenges of today, tomorrow, and many years to come.
About the team
Today, data scientists piece together data, tooling, and frameworks to get bespoke data science workloads running and producing business value. Data scientists then hand off models to engineering teams to attempt to deploy them to production. These teams speak different languages, use different tools, and have completely different workflows. This makes it very difficult to deploy data science workloads to production, increasing time to value and costs. One of our primary goals for our ModelOps stage is to reduce the complexities of data science workloads and integrate these workloads to easily be managed and developed within GitLab.
How GitLab will support you
- All remote, asynchronous work environment
- Unlimited PTO (paid time off)
- GitLab is home to many dedicated Team Member Resource Groups
- Benefits to manage your health, wealth, and well-being regardless of location
- Equity compensation & Employee Stock Purchase Plan offered
- A personal growth and development budget per year
- Parental leave: 16 weeks
- Home office support
#LI-MD5
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.
Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us.
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.
We're the company behind GitLab, The DevSecOps Platform for software innovation.
What started in 2011 as an open source project to help one team of programmers collaborate is now the platform millions of people use to deliver software faster, more efficiently, while strengthening security and compliance.
Since the beginning, we've been firm believers in remote work, open source, DevOps, and iteration. We get up and log on in the morning (or whenever we choose to start our days) to work alongside the GitLab community to deliver new innovations every month that help teams focus on shipping great code faster, not their toolchain.
