🛠 Tech Stack

💼 About This Role

You'll design and optimize large-scale AI pre-training pipelines for advanced language and multi-modal models. Your core impact will be developing novel architectures and solving complex computational bottlenecks that push model intelligence and efficiency. This role offers access to cutting-edge GPU infrastructure and collaboration with world-class researchers.

🎯 What You'll Do

• Design large-scale AI pre-training pipelines across distributed GPU infrastructures.
• Prototype and optimize architectures for large language and multi-modal models.
• Conduct experiments, analyze results, and iterate on training methodologies.
• Resolve bottlenecks in model performance, scalability, and computational optimization.

📋 Requirements

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

✨ Nice to Have

• Experience with data curation and baseline improvements.
• Familiarity with distributed computing and parallel training strategies.
• Advanced degree in Computer Science, AI, or related field.

🎁 Benefits & Perks

• 🏖️ Fully remote work environment.
• 💻 Cutting-edge AI research opportunity.
• ⚡ Access to high-performance GPU clusters.
• 🌍 Global collaborative culture.
• 📈 Professional growth in AI and blockchain ecosystems.

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter call· 30 min
2. 2Technical interview· 60 min
3. 3Onsite/team interview· 60 min