🛠 Tech Stack

💼 About This Role

You'll design and optimize large-scale AI pre-training pipelines for advanced language and multi-modal models. Your work will directly improve model intelligence, efficiency, and scalability through novel architectures and training methodologies. This role offers access to thousands of GPUs in a research-driven, globally distributed environment.

🎯 What You'll Do

• Design and optimize large-scale AI pre-training pipelines on distributed GPU infrastructure.
• Research and prototype advanced architectures for language and multi-modal models.
• Analyze training results and iterate on methodologies to improve model quality.
• Resolve performance, scalability, and computational optimization bottlenecks.

📋 Requirements

• Strong experience with large language models and transformer architectures.
• Deep understanding of distributed machine learning and large-scale GPU 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.
• Experience with data curation for pre-training.
• Advanced degree in Computer Science or related field.

🎁 Benefits & Perks

• 🌍 Fully remote work environment.
• 🔬 Cutting-edge AI research on large-scale pre-training.
• 💻 Advanced GPU clusters and high-performance computing.
• 🌐 Global collaborative culture with top researchers and engineers.
• 🚀 Fast-paced, innovation-driven environment.

📨 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