Updated on 5/25/2023
Google Cloud Platform
- 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
- 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
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- Spending Company Money
- Equity Compensation
- Life Insurance
- Financial Wellness
- Paid Time Off
- Growth and Development Benefit
- GitLab Contribute
- Business Travel Accident Policy
- Employee Assistance Program
- Part-time contracts
- Meal Train
- Fertility & Family Planning
- Parental Leave
Company Core Values
- Collaboration: To achieve results, team members must work together effectively.
- Results: We do what we promised to each other, customers, users, and investors.
- Efficiency: Working efficiently on the right things enables us to make fast progress, which makes our work more fulfilling.
- Diversity, Inclusion, and Belonging.
- Iteration: We do the smallest thing possible and get it out as quickly as possible.
- Transparency: Be open about as many things as possible.