🛠 Tech Stack

💼 About This Role

You'll design and optimize large-scale AI model pre-training pipelines across distributed GPU infrastructures. Your core impact involves researching novel architectures for language and multi-modal models, driving breakthroughs in efficiency and scalability. You'll collaborate with world-class engineers leveraging cutting-edge compute clusters.

🎯 What You'll Do

• Design and optimize large-scale AI model pre-training pipelines.
• Research and prototype advanced architectures for LLMs and multi-modal AI.
• Analyze training results and iterate on methodologies to improve model quality.
• Resolve bottlenecks related to model performance, scalability, and optimization.

📋 Requirements

• large language models and transformer architectures experience
• distributed machine learning and GPU-based training expertise
• PyTorch, TensorFlow, or JAX proficiency
• deep learning optimization and model scaling skills

✨ Nice to Have

• Advanced degree in CS, AI, or ML
• Experience with parallel training strategies

🎁 Benefits & Perks

• 🏠 Fully remote work
• 💻 Cutting-edge AI research on large-scale pre-training
• ⚡ Access to high-performance GPU clusters
• 🌍 Global collaborative culture with world-class talent
• 🚀 Fast-paced innovation-driven environment

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Interview· 60 min
3. 3Offer· 30 min