Job Description
We are at the precipice of a new era in human-computer interaction. At Zai Dynamics, we are building the foundational layers of the metaverse and synthetic reality, leveraging the most advanced generative AI technologies available today. As our Director of Generative Reality & AI Ethics, you will lead the charge in architecting systems that blur the line between the digital and physical worlds.
Your role is pivotal in defining not just how we build these technologies, but ensuring they align with humanity's core values. You will oversee the research, development, and deployment of next-generation synthetic media, ensuring our products are not only technologically superior but also ethically sound and transparent.
If you are a visionary engineer with a passion for the future of AI and a commitment to ethical standards, we want to hear from you.
Responsibilities
- Architect Scalable AI Pipelines: Design and implement robust deep learning architectures for real-time, high-fidelity synthetic media generation.
- Define Ethical Frameworks: Establish comprehensive guidelines for AI bias, transparency, and fairness in all generative outputs.
- Lead Technical Strategy: Guide a cross-disciplinary team of AI researchers, data scientists, and engineers in pursuing cutting-edge research.
- Model Optimization: Optimize generative models for performance and latency, deploying them on next-generation hardware accelerators.
- Stakeholder Collaboration: Work closely with product and creative teams to integrate generative AI into consumer-facing experiences seamlessly.
- R&D Leadership: Stay ahead of the curve by prototyping novel algorithms in areas such as diffusion models and neural rendering.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, or a related field with a focus on Machine Learning or Computer Vision.
- Experience: 10+ years of experience in software engineering and leading high-impact machine learning projects.
- Technical Skills: Deep expertise in PyTorch, TensorFlow, or JAX; proven track record with large language models (LLMs) and diffusion models.
- Architecture: Strong understanding of distributed systems, cloud infrastructure (AWS/GCP), and MLOps practices.
- Leadership: Demonstrated ability to mentor engineering teams and drive a technical vision from conception to production.
- Communication: Excellent verbal and written communication skills, capable of explaining complex technical concepts to diverse audiences.