Job Description
We are Nexus Horizon Technologies, a pioneer in next-generation artificial intelligence. As we accelerate toward the 2026 horizon, we are seeking a visionary Lead AI Architect to spearhead the development of our flagship autonomous agent ecosystem. This is not just a job; it is a mission to redefine human-machine collaboration in a post-AI-native world.
In this high-impact role, you will bridge the gap between theoretical research and production-scale deployment. You will be responsible for architecting the neural infrastructure that powers our multimodal agents, ensuring they are safe, efficient, and capable of reasoning in complex environments.
Join us in building the intelligence layer for the future. You will work with a world-class team of researchers, engineers, and ethicists, utilizing state-of-the-art tools and methodologies to solve problems that were previously deemed unsolvable.
Responsibilities
- Architect Scalable ML Infrastructure: Design and implement robust, distributed machine learning pipelines capable of handling petabyte-scale data streams with sub-millisecond latency.
- Lead R&D in Generative Models: Direct research initiatives into next-generation Large Language Models (LLMs) and diffusion models, focusing on reasoning, memory retention, and world modeling.
- Optimize Model Inference: Engineer efficient model quantization and pruning strategies to deploy high-performance AI models on edge devices and cloud environments.
- Ethical AI Implementation: Establish and enforce rigorous safety protocols and alignment strategies to ensure AI behaviors remain beneficial and unbiased.
- Technical Mentorship: Mentor a team of senior engineers and data scientists, fostering a culture of innovation, continuous learning, and technical excellence.
- System Integration: Integrate diverse AI modules (vision, NLP, robotics) into a cohesive, autonomous operating system.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Mathematics, or a related field, with a focus on Artificial Intelligence or Machine Learning.
- Experience: 7+ years of experience in software engineering and machine learning, with at least 3 years in a leadership or senior architect role.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and CUDA. Deep understanding of transformer architectures and attention mechanisms.
- System Design: Proven track record of designing scalable, fault-tolerant distributed systems (Kubernetes, AWS/GCP, Spark).
- Research Publication: Demonstrated ability to conduct original research and publish findings in top-tier conferences (NeurIPS, ICML, ICLR).
- Problem Solving: Exceptional ability to debug complex, low-level system issues and optimize deep learning workloads.