🛠 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'll conduct experiments, analyze results, and resolve performance bottlenecks to improve model efficiency and scalability. This role offers access to cutting-edge GPU infrastructure and collaboration with world-class researchers in a fully remote, innovation-driven environment.

🎯 What You'll Do

• Design and optimize large-scale AI model pre-training pipelines.
• Research and prototype advanced architectures for LLMs and multi-modal AI.
• Conduct experiments and iterate on training methodologies.
• Identify and resolve performance and scalability bottlenecks.
• Contribute to data curation strategies and baseline improvements.

📋 Requirements

• Large language models and transformer architectures experience.
• Distributed ML systems and large-scale GPU training expertise.
• Proficiency in PyTorch, TensorFlow, or JAX.
• Deep learning optimization and model scaling experience.

✨ Nice to Have

• Experience with parallel training strategies and infrastructure optimization.
• Advanced degree in CS, AI, or ML.
• Research-oriented mindset and ability to explore novel techniques.

🎁 Benefits & Perks

• 🌍 Fully remote work from anywhere.
• 🔬 Cutting-edge AI research on large-scale pre-training systems.
• ⚡ Access to high-performance GPU clusters.
• 🤝 Collaborative global culture with world-class talent.
• 🚀 Fast-paced innovation-driven environment.

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter call· 30 min
2. 2Technical interview· 60 min
3. 3Offer· 15 min