Job Description
We are building the foundational infrastructure for the technological landscape of 2026. We are seeking a visionary Senior AI Architect to lead the research and development of next-generation Artificial General Intelligence (AGI) systems. If you are passionate about pushing the boundaries of what is possible in machine learning and want to define the roadmap for the future, this is your opportunity to shape history.
At Zai Future Systems, we don't just predict the future; we engineer it. You will work alongside the brightest minds in the industry to solve complex challenges in reasoning, scalability, and human-AI interaction.
Responsibilities
- Architect AGI Infrastructure: Design and build scalable, high-performance neural network architectures capable of handling complex, multi-modal tasks.
- Lead R&D Initiatives: Spearhead research projects focused on breakthroughs in machine learning efficiency, transfer learning, and reasoning capabilities.
- Roadmap Execution: Translate strategic 2026 product goals into actionable technical roadmaps and engineering milestones.
- Model Optimization: Optimize large language models (LLMs) and transformer architectures for deployment on edge devices and massive distributed clusters.
- Tech Stack Leadership: Establish best practices for code quality, reproducibility, and experimentation within the AI research organization.
- Mentorship: Guide and mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, Statistics, or a related field with a focus on AI/ML.
- Experience: 10+ years of experience in machine learning engineering and large-scale distributed system architecture.
- Technical Skills: Deep proficiency in Python, PyTorch, TensorFlow, and JAX.
- Research Track Record: Proven history of publishing research in top-tier conferences (NeurIPS, ICML, ICLR, ACL) or holding patents in AI/ML.
- Specialized Knowledge: Extensive experience with Generative AI, Transformers, Reinforcement Learning (RLHF), and Bayesian methods.
- Problem Solving: Ability to tackle ambiguous problems and derive novel solutions for futuristic challenges.