🛠 Tech Stack

💼 About This Role

You'll lead the architecture and evolution of a cloud-native platform that serves production-grade AI models. Your work will directly impact media algorithms used by millions, bridging research and product innovation. You'll design GPU-aware systems and drive MLOps best practices.

🎯 What You'll Do

• Own architecture, stability, scalability, and performance of the platform.
• Design and implement features for synchronous and asynchronous algorithm execution.
• Enhance GPU management, scheduling, and resource allocation.
• Act as technical bridge between Research and Application teams.

📋 Requirements

• 8+ years of experience with 3+ years in ML/AI or GPU infrastructure.
• Proficiency in Python and familiarity with Ruby or Go.
• Strong understanding of Kubernetes internals and GPU workloads.
• In-depth knowledge of AWS services.

✨ Nice to Have

• Experience in research-driven environments with data scientists or ML engineers.
• Contributions to open-source projects for model serving or Kubernetes operators.
• Experience supporting diverse user groups across engineering and research.

🎁 Benefits & Perks

• 🏖️ Unlimited PTO
• 📈 Stock options
• 🏥 Health insurance
• 💻 Remote flexibility
• 📚 Learning budget