Job Description
We are seeking a visionary Senior AI Architect 2026 to lead the next generation of artificial intelligence systems. At Zai Future Tech, we are building the foundational technologies that will define the era of autonomous, scalable intelligence. If you are passionate about pushing the boundaries of machine learning, deep learning, and future-forward software architecture, we want to hear from you.
In this role, you will not just implement existing models; you will architect the infrastructure for the future. You will work at the intersection of research and production, ensuring our systems are robust, secure, and ready for the demands of 2026 and beyond.
Why Join Us?
- Work on cutting-edge generative AI and autonomous agents.
- Competitive compensation package with equity options.
- Flexible remote-first culture with a premium office in San Francisco.
- Access to top-tier hardware and research talent.
Responsibilities
- Design and deploy scalable machine learning pipelines and infrastructure capable of handling petabyte-scale data.
- Lead the technical roadmap for AI model development, focusing on generative AI and reinforcement learning for 2026 objectives.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate business needs into technical solutions.
- Optimize model inference speed and reduce latency to ensure real-time user experiences.
- Mentor junior architects and engineers, fostering a culture of innovation and technical excellence.
- Ensure the security, privacy, and ethical use of AI data within the system architecture.
- Stay ahead of industry trends in AI, quantum computing integration, and edge computing.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related field.
- 10+ years of professional experience in software engineering and machine learning architecture.
- Expert proficiency in Python, C++, and modern deep learning frameworks (PyTorch, TensorFlow, JAX).
- Proven experience designing large-scale distributed systems and cloud-native architectures (AWS, GCP, or Azure).
- Strong background in Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Experience with MLOps, model versioning, and automated deployment pipelines.
- Exceptional problem-solving skills and the ability to thrive in a fast-paced, high-stakes environment.