Job Description
The Future is Here. Are You Ready to Architect It?
We are looking for a visionary Next-Gen AI Architect to join Zenith Future Labs. We are not just building software; we are engineering the fabric of tomorrow. As we approach the pivotal year of 2026, we are pioneering the integration of neuromorphic computing, quantum-assisted learning, and autonomous decision-making systems.
In this high-impact role, you will lead the architectural vision for our flagship AI initiatives, ensuring our systems are scalable, secure, and ethically aligned. You will work at the intersection of deep learning, distributed systems, and next-generation hardware to solve problems that were previously thought impossible.
Why Join Us?
- Work on cutting-edge projects that define the trajectory of Artificial General Intelligence (AGI).
- Competitive compensation package with performance-based equity.
- Flexible remote-first culture with state-of-the-art office amenities in San Francisco.
Responsibilities
- Design and deploy scalable, fault-tolerant AI infrastructure capable of processing exabyte-scale data streams.
- Lead research and implementation of neuromorphic algorithms and quantum machine learning interfaces.
- Collaborate with a multidisciplinary team of ethicists, physicists, and software engineers to ensure AI safety and alignment.
- Optimize neural network architectures for real-time edge computing environments and massive throughput.
- Establish and mentor best practices for MLOps, AI governance, and code quality within the organization.
- Define technical roadmaps for AI adoption, ensuring alignment with the company’s 2026 strategic vision.
Qualifications
- PhD or Master’s degree in Computer Science, Computational Neuroscience, Applied Mathematics, or a related field.
- Extensive experience building large-scale Deep Learning models using PyTorch, TensorFlow, or JAX.
- Proven track record of deploying AI solutions in production environments with high availability and low latency.
- Strong understanding of distributed systems theory, microservices, and cloud infrastructure (AWS, GCP, Azure).
- Familiarity with next-generation hardware acceleration (e.g., GPU/TPU clusters, FPGA, Neuromorphic chips).