🛠 Tech Stack

💼 About This Role

You'll design and optimize large-scale AI model pre-training pipelines across distributed GPU infrastructures. You'll research and prototype advanced architectures for language and multi-modal models, independently conducting experiments to improve model quality and efficiency. This is an opportunity to contribute to breakthroughs in AI within a globally distributed, 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 systems.
• Conduct experiments and iterate on methodologies to improve model quality.
• Identify and resolve bottlenecks in model performance and scalability.
• Contribute to data curation strategies and baseline improvements.

📋 Requirements

• Large language models and transformer architectures experience.
• Distributed machine learning and large-scale GPU training expertise.
• Proficiency in PyTorch, TensorFlow, or JAX.
• Strong Python programming and scalable AI training system building skills.

✨ Nice to Have

• Advanced degree in CS, AI, or Machine Learning.
• Research-oriented mindset with novel technique exploration.
• Familiarity with parallel training strategies and infrastructure optimization.

🎁 Benefits & Perks

• 🏖️ Fully remote work from anywhere.
• 🔬 Cutting-edge AI research on large-scale pre-training systems.
• ⚡ Access to high-performance GPU clusters.
• 🌍 Global collaborative 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. 3Hiring Manager Interview· 45 min