🛠 Tech Stack

💼 About This Role

You'll design and optimize large-scale AI model pre-training pipelines across distributed GPU infrastructures. Your work will directly impact breakthroughs in model intelligence, efficiency, and scalability. You'll collaborate with world-class engineers and researchers, leveraging cutting-edge infrastructure.

🎯 What You'll Do

• Design, develop, 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
• Identify and resolve bottlenecks in model performance and scalability

📋 Requirements

• Strong experience working with large language models and transformer architectures
• Deep understanding of distributed machine learning systems and GPU-based training
• Proven expertise in PyTorch, TensorFlow, or JAX
• Solid background in deep learning optimization and model scaling

✨ Nice to Have

• Advanced degree in Computer Science, AI, or related field
• Experience with data curation strategies for training

🎁 Benefits & Perks

• 🏖️ Fully remote work
• 💻 Cutting-edge AI research on large-scale pre-training
• 🔬 Access to high-performance GPU clusters
• 🌍 Collaborative global culture with top talent
• 🚀 Autonomous and innovation-driven environment

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Interview· 60 min
3. 3Research Presentation· 45 min