🛠 Tech Stack

💼 About This Role

You'll work on large-scale pre-training for advanced language and multi-modal models, shaping breakthroughs in model intelligence, efficiency, and scalability. Collaborate with world-class engineers using cutting-edge GPU infrastructure.

🎯 What You'll Do

• Design and optimize pre-training pipelines across distributed GPU infrastructures.
• Research and prototype advanced architectures for LLMs and multi-modal models.
• Analyze training results and iterate on methodologies to improve model quality.
• Identify and resolve bottlenecks in model performance and computational optimization.

📋 Requirements

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

✨ Nice to Have

• Experience with data curation strategies for pre-training.
• Familiarity with parallel training strategies and infrastructure optimization.
• Advanced degree in Computer Science, AI, or related field.

🎁 Benefits & Perks

• 🏖️ Fully remote work environment with location flexibility.
• 🖥️ Access to advanced computing infrastructure and high-performance GPU clusters.
• 🌍 Collaborative global culture with world-class engineering talent.
• 🚀 Fast-paced innovation focused on pushing AI boundaries.
• 📈 Professional growth in rapidly evolving AI and blockchain ecosystems.

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Interview· 60 min
3. 3Team Interview· 45 min
4. 4Offer· 30 min