Job Description
We are at the forefront of defining the technological landscape of 2026 and beyond. Nexus Horizon Technologies is seeking a visionary Senior AI Architect to lead the development of next-generation Artificial General Intelligence (AGI) systems. You will not just be writing code; you will be architecting the cognitive infrastructure of the future. If you are passionate about pushing the boundaries of Large Language Models (LLMs), autonomous agents, and ethical AI alignment, this is your opportunity to shape the trajectory of human-machine interaction.
Why Join Us?
- Impact at Scale: Your work will directly influence the core systems used by millions globally.
- Premium Compensation: Competitive salary and equity packages for top-tier talent.
- Innovation First: Access to cutting-edge hardware and proprietary datasets.
Responsibilities
- Architect Next-Gen Models: Design and implement scalable architectures for Large Language Models and multimodal AI systems focused on 2026 capabilities.
- Optimization & Efficiency: Drive research into model compression, quantization, and inference optimization to reduce latency and resource consumption.
- Autonomous Agent Systems: Develop the logic and reasoning frameworks that enable AI agents to perform complex, multi-step tasks in dynamic environments.
- Research & Publication: Collaborate with academic institutions to publish breakthroughs in deep learning, causal inference, and reinforcement learning.
- Ethical AI Implementation: Establish rigorous guardrails and alignment protocols to ensure AI safety and bias mitigation.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 7+ years of professional experience in deep learning, NLP, or AI research.
- Technical Mastery: Expert-level proficiency in Python, PyTorch, or TensorFlow, with a deep understanding of Transformer architectures.
- Research Background: Proven track record of publishing in top-tier conferences (NeurIPS, ICML, ICLR) or leading internal R&D initiatives.
- System Design: Demonstrated ability to design production-grade ML systems that handle high concurrency and scale.
- Creative Problem Solving: Ability to tackle ambiguous, high-complexity problems with innovative algorithmic solutions.