Job Description
Are you ready to define the technology landscape of 2026? Neural Horizon is seeking a visionary Senior AI Architect to lead our cutting-edge research division. In this role, you won't just build models; you will architect the fundamental systems that power the next generation of sentient digital intelligence. If you are obsessed with pushing the boundaries of Generative AI, Quantum Computing integration, and Ethical Machine Learning, we want to hear from you.
Why join us?
We are building the operating system for the future. Our mission is to accelerate the singularity through ethical, scalable, and hyper-efficient AI systems. You will work directly with industry pioneers and have the autonomy to define the technical roadmap for our flagship 2026 Vision platform.
Responsibilities
- Design and deploy scalable, distributed AI infrastructure capable of processing exabyte-scale data streams in real-time.
- Lead a team of elite data scientists and ML engineers in pioneering research for AGI (Artificial General Intelligence) pathways and neural-symbolic integration.
- Optimize deep learning models for inference on next-gen hardware architectures, ensuring maximum energy efficiency and speed.
- Establish best practices for MLOps, CI/CD pipelines, and model governance to ensure reliability and reproducibility.
- Collaborate with cross-functional teams (Product, Engineering, and Ethics Boards) to translate complex scientific concepts into actionable product features.
- Present technical strategy to executive stakeholders and influence long-term product vision.
Qualifications
- PhD or Master's degree in Computer Science, Mathematics, Statistics, or a related technical field (or equivalent professional experience).
- 10+ years of experience in machine learning, deep learning, or AI research with a proven track record of shipping high-impact products.
- Expert proficiency in Python, PyTorch, TensorFlow, and C++ for performance optimization.
- Deep understanding of Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Experience with cloud platforms (AWS/GCP/Azure) and containerization technologies (Kubernetes, Docker).
- Strong background in distributed systems and high-availability architecture.