Job Description
At Nexus Horizon Technologies, we aren't just building software; we are architecting the digital reality of tomorrow. As we prepare to redefine the technological landscape for the 2026 era, we are seeking a visionary AI Systems Architect & Future Strategist to lead our advanced engineering division.
In this pivotal role, you will bridge the gap between theoretical artificial intelligence and practical, scalable systems. You will work on cutting-edge projects involving autonomous decision-making systems, neural architecture search, and the ethical implementation of AGI (Artificial General Intelligence) prototypes.
We are looking for a thinker who not only understands code but also understands the trajectory of human-machine collaboration. If you are ready to push the boundaries of what is possible in 2026 and beyond, we want to hear from you.
Responsibilities
- Design and implement scalable, fault-tolerant AI infrastructure capable of processing exabytes of data in real-time.
- Define the long-term architectural roadmap for our proprietary AI models, ensuring alignment with 2026 industry standards.
- Lead the integration of quantum computing principles into classical machine learning pipelines.
- Establish frameworks for ethical AI governance and bias mitigation in algorithmic decision-making.
- Collaborate with cross-functional teams of data scientists, security experts, and product managers to translate complex algorithms into user-centric solutions.
- Oversee the performance tuning of neural networks and optimize inference speeds for edge devices.
Qualifications
- Master’s or Ph.D. degree in Computer Science, Artificial Intelligence, or a related technical field, or equivalent extensive industry experience.
- Minimum of 8+ years of professional experience in machine learning engineering, with at least 3 years in a senior architecture role.
- Deep expertise in deep learning frameworks (TensorFlow, PyTorch, JAX) and distributed computing systems (Kubernetes, Docker).
- Proven track record of deploying large-scale AI models in production environments.
- Strong understanding of natural language processing (NLP) and computer vision architectures.
- Excellent verbal and written communication skills with the ability to explain complex technical concepts to non-technical stakeholders.