Job Description
Are you ready to architect the future of intelligence?
Nexus Horizons is seeking a visionary Senior AI Architect to lead the development of our proprietary 2026 Vision architecture. As we stand on the precipice of the next industrial revolution, we need a technical leader who can bridge the gap between theoretical AI breakthroughs and scalable, real-world applications. You will define the blueprint for the next generation of autonomous systems, ensuring our technology remains ahead of the curve.
In this role, you will not just write code; you will shape the ethical framework and technical standards of the industry.
Why Nexus Horizons?
• Be at the forefront of Generative AI and Quantum Machine Learning.
• Competitive equity package and top-tier health benefits.
• Remote-first culture with quarterly global summits.
The Role:
We are looking for an expert to design resilient, low-latency neural networks capable of processing petabytes of real-time data. You will work closely with our R&D labs and product teams to integrate cutting-edge LLMs with edge computing devices.
Responsibilities
- Design and implement scalable AI architectures for our 2026 roadmap, focusing on Large Language Models (LLMs) and generative adversarial networks.
- Lead the technical strategy for integrating quantum computing primitives into classical machine learning pipelines.
- Establish best practices for data privacy, model interpretability, and ethical AI usage.
- Collaborate with cross-functional teams to translate complex research concepts into production-ready software.
- Mentor junior architects and data scientists, fostering a culture of continuous innovation.
- Conduct rigorous code reviews and performance optimization for large-scale distributed systems.
Qualifications
- 5+ years of experience in machine learning engineering, with a focus on deep learning frameworks (TensorFlow, PyTorch, JAX).
- Proven track record of deploying high-impact AI models to production environments at scale.
- Strong proficiency in Python, C++, and distributed systems architecture.
- Experience with MLOps tools (Kubernetes, Airflow, MLflow) and cloud platforms (AWS, GCP, Azure).
- Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, or a related field is preferred.
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.