Job Description
Join the Architects of Tomorrow.
Zai Future Labs is pioneering the 2026 AI revolution. We are seeking a visionary Senior Generative AI Architect to lead the development of next-generation autonomous agents and large-scale generative models. If you are passionate about shaping the future of technology and building systems that redefine human-machine interaction, we want to hear from you.
In this pivotal role, you will design scalable, ethical, and high-performance AI architectures that power our flagship products. You will work at the intersection of deep learning, data science, and cloud infrastructure, collaborating with top-tier engineers to push the boundaries of what's possible.
Responsibilities
- Architectural Leadership: Design and oversee the implementation of robust Generative AI architectures, including LLMs and diffusion models, tailored for enterprise scalability.
- Model Optimization: Fine-tune and optimize pre-trained models for specific niche applications, significantly improving inference speed and accuracy.
- Infrastructure Strategy: Build and maintain high-performance data pipelines and MLOps infrastructure on AWS/GCP to support continuous model deployment.
- Ethical AI Oversight: Lead initiatives to ensure model fairness, transparency, and safety, adhering to the highest industry standards for responsible AI.
- Research & Innovation: Stay at the forefront of AI research (e.g., reinforcement learning from human feedback, multimodal learning) and integrate cutting-edge advancements into our roadmap.
- Team Mentorship: Mentor junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Mathematics, or a related field, with a focus on Machine Learning or Artificial Intelligence.
- Experience: 5+ years of professional experience in software engineering, with at least 3 years specifically focused on Machine Learning and Deep Learning.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and experience with Hugging Face Transformers.
- Cloud Expertise: Strong background in cloud-native development and MLOps tools (e.g., Kubeflow, MLflow, Docker, Kubernetes).
- Problem Solving: Demonstrated ability to solve complex, unstructured problems and translate business requirements into technical solutions.
- Communication: Excellent verbal and written communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.