Job Description
Welcome to Zai Frontier Tech, a pioneer in next-generation intelligence systems. As we accelerate toward the 2026 technological paradigm, we are seeking a visionary Lead AI Architect to design the neural infrastructure that will define the next decade of human-computer interaction.
In this pivotal role, you will not just build models; you will architect the future of scalable, generative AI ecosystems. We are looking for a strategic thinker who combines deep technical mastery with a passion for pushing the boundaries of what is possible in AI development.
Why Join Us?
- Work on the 2026 Tech Stack - cutting-edge frameworks and protocols.
- Competitive compensation and equity package.
- Flexible remote-first culture with premium health benefits.
- Opportunity to shape the industry standard for Generative AI.
Responsibilities
- Architect and deploy scalable large-scale language models (LLMs) and multi-modal AI systems optimized for the 2026 era.
- Lead a high-performing team of ML engineers and data scientists in research, development, and production deployment.
- Define technical roadmaps and establish best practices for model training, fine-tuning, and evaluation.
- Collaborate with cross-functional product teams to integrate advanced AI capabilities into consumer and enterprise solutions.
- Ensure system resilience, security, and ethical AI compliance across all deployed infrastructure.
- Prioritize research into novel algorithms to maintain a competitive edge in the 2026 landscape.
Qualifications
- Master’s degree or PhD in Computer Science, Mathematics, or a related field; equivalent practical experience is highly valued.
- 10+ years of experience in software engineering and machine learning, with at least 5 years in a leadership or architectural role.
- Deep expertise in Python, PyTorch, TensorFlow, and modern GPU acceleration frameworks.
- Proven track record of deploying production-grade AI models handling billions of parameters.
- Strong understanding of NLP, Computer Vision, and Reinforcement Learning principles.
- Experience with cloud infrastructure (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).