🛠 Tech Stack

💼 About This Role

You'll design and optimize large-scale AI model pre-training pipelines for advanced language and multi-modal systems. You will conduct experiments to improve model quality and efficiency, and resolve computational bottlenecks. This role offers access to thousands of GPUs and the chance to collaborate with world-class engineers and researchers in a fast-moving, research-driven environment.

🎯 What You'll Do

• Design, develop, and optimize large-scale pre-training pipelines for AI models.
• Research and prototype advanced architectures for LLMs and multi-modal systems.
• Conduct experiments and iterate on methodologies to improve model quality.
• Resolve bottlenecks related to model performance and computational optimization.

📋 Requirements

• Strong experience 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

• Familiarity with distributed computing and parallel training strategies.
• Research-oriented mindset and ability to explore novel techniques.
• Advanced degree in Computer Science, AI, or Machine Learning.

🎁 Benefits & Perks

• 🏠 Fully remote work environment.
• ⚡ Cutting-edge AI research and large-scale pre-training systems.
• 🖥️ Access to high-performance GPU clusters and advanced infrastructure.
• 🌍 Collaborative global culture with world-class engineering talent.
• 📈 Professional growth in AI and blockchain ecosystems.

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Interview· 45 min