Job Description
We are at the precipice of a new era in artificial intelligence, and Zai Systems is leading the charge toward the technological landscape of 2026. We are seeking a visionary Lead AI Architect to design and implement the next generation of generative models and autonomous systems. If you thrive in high-stakes environments and want to shape the future of AI infrastructure, this is your opportunity.
In this role, you will bridge the gap between theoretical breakthroughs and scalable production systems, ensuring our technology remains ahead of the curve for the years to come.
Responsibilities
- Architect Scalable AI Infrastructure: Design and oversee the development of robust ML pipelines optimized for the computational demands of 2026.
- Model Innovation: Lead the research and deployment of cutting-edge generative models, pushing the boundaries of LLM capabilities and efficiency.
- Team Leadership: Mentor a world-class team of data scientists and engineers, fostering a culture of innovation and technical excellence.
- Strategic Roadmapping: Define the technical vision and long-term roadmap for AI integration within core product ecosystems.
- Performance Optimization: Drive initiatives to reduce inference latency and improve model accuracy in real-time environments.
- Cross-Functional Collaboration: Partner with product managers and engineering leads to translate complex AI capabilities into user-centric features.
Qualifications
- Education: MS or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 8+ years of experience in software engineering with a focus on AI/ML, including 3+ years in a leadership or architectural role.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and experience with distributed computing frameworks (Kubernetes, Ray).
- 2026 Vision: Deep understanding of emerging AI paradigms, including self-supervised learning and multimodal AI architectures.
- Communication: Exceptional ability to communicate complex technical concepts to diverse stakeholders.
- Problem Solving: Demonstrated history of solving complex, large-scale engineering challenges.