Job Description
Are you ready to architect the intelligence of tomorrow?
At Nexus Horizon Labs, we aren't just building software; we are engineering the fabric of the next technological era. As a Senior AI Architect, you will spearhead the development of Autonomous Agentic Systems and Generative Neural Networks designed for the year 2026 and beyond. We are looking for visionaries who understand the intersection of deep learning, systems engineering, and futuristic scalability.
If you thrive in a fast-paced environment and want to define the standard for AI architecture in the coming decade, this is your opportunity to lead from the front.
At Nexus Horizon Labs, we aren't just building software; we are engineering the fabric of the next technological era. As a Senior AI Architect, you will spearhead the development of Autonomous Agentic Systems and Generative Neural Networks designed for the year 2026 and beyond. We are looking for visionaries who understand the intersection of deep learning, systems engineering, and futuristic scalability.
If you thrive in a fast-paced environment and want to define the standard for AI architecture in the coming decade, this is your opportunity to lead from the front.
Responsibilities
- Design and deploy scalable neural architectures for next-gen Large Language Models (LLMs) and Transformer variants.
- Optimize inference pipelines for high-throughput, low-latency environments using edge computing and distributed systems.
- Collaborate with quantum computing research teams to integrate classical and quantum machine learning paradigms.
- Establish best practices for AI safety, ethics, and interpretability in autonomous agents.
- Lead technical strategy for multi-modal AI systems processing text, vision, and audio simultaneously.
- Mentor junior engineers and data scientists in advanced deep learning methodologies.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, Statistics, or a related technical field.
- 5+ years of hands-on experience building and scaling production-level AI/ML systems.
- Deep expertise in PyTorch, TensorFlow, or JAX with a focus on custom layer development.
- Proficiency in systems programming languages such as Rust, C++, or Go for performance optimization.
- Strong understanding of distributed systems, cloud infrastructure (AWS/GCP), and containerization (Docker/K8s).
- Proven track record of deploying AI models that handle high concurrency and real-time data streams.