🛠 Tech Stack

💼 About This Role

You'll design and optimize large-scale pre-training pipelines for advanced language and multi-modal models. You'll conduct experiments and resolve computational bottlenecks using thousands of GPUs, shaping breakthroughs in model intelligence and scalability. This role offers the chance to contribute to cutting-edge AI in a fully remote, globally distributed environment.

🎯 What You'll Do

• Design and optimize large-scale AI model pre-training pipelines on distributed GPU clusters
• Research and prototype novel architectures for LLMs and multi-modal AI systems
• Conduct experiments and iterate on training methodologies to improve model quality
• Resolve performance bottlenecks related to model scalability and computational efficiency

📋 Requirements

• Strong experience with large language models and transformer architectures
• Deep understanding of distributed GPU-based 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 strategies for pre-training
• Familiarity with parallel training strategies and infrastructure optimization
• Advanced degree in Computer Science or related field

🎁 Benefits & Perks

• 🏠 Fully remote work environment
• 🖥️ Access to advanced GPU clusters
• 🌍 Collaborative global culture with top researchers
• 🚀 Fast-paced innovation-driven atmosphere
• 📈 Professional growth opportunities in AI ecosystems

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3On-site / Final Round· 60 min