AI Research Engineer - Pre training

Overview

Accountabilities

• Design, develop, and optimize large-scale AI model pre-training pipelines across distributed GPU infrastructures.
• Research and prototype advanced architectures for large language models and multi-modal AI systems.
• Conduct experiments independently and collaboratively, analyze training results, and iterate on methodologies to improve model quality and efficiency.
• Identify, investigate, and resolve bottlenecks related to model performance, scalability, and computational optimization.
• Contribute to data curation strategies and baseline improvements to strengthen model training outcomes.
• Enhance distributed training systems to ensure seamless scalability, reliability, and operational efficiency across large compute environments.
• Collaborate with cross-functional engineering and research teams to accelerate innovation and deliver high-impact AI capabilities.
• Stay informed on emerging trends and advancements in AI research, machine learning systems, and large-scale model training.

Requirements

• Strong experience working with large language models, transformer architectures, and AI pre-training methodologies.
• Deep understanding of distributed machine learning systems and large-scale GPU-based training environments.
• Proven expertise in machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar technologies.
• Solid background in deep learning optimization, model scaling, and performance tuning.
• Experience designing and executing research experiments with strong analytical and problem-solving capabilities.
• Familiarity with distributed computing, parallel training strategies, and infrastructure optimization.
• Strong programming skills in Python and experience building scalable AI training systems.
• Research-oriented mindset with curiosity, innovation, and the ability to explore novel techniques and architectures.
• Excellent communication and collaboration skills within remote and international teams.
• Advanced degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field is preferred.

Benefits

• Fully remote work environment with the flexibility to work from anywhere.
• Opportunity to work on cutting-edge AI research and large-scale pre-training systems.
• Access to advanced computing infrastructure and high-performance GPU clusters.
• Collaborative global culture with exposure to world-class engineering and research talent.
• Fast-paced and innovation-driven environment focused on pushing technological boundaries.
• Opportunity to contribute to impactful products shaping the future of digital finance, AI, and decentralized technologies.
• Professional growth opportunities within rapidly evolving AI and blockchain ecosystems.
• Flexible and autonomous work culture that values creativity, experimentation, and ownership.

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