Job Description
We are defining the infrastructure of tomorrow. Nexus Horizon Labs is seeking a visionary Senior AI Systems Architect to lead the development of the AI frameworks required for the 2026 era. In this role, you will bridge the gap between theoretical breakthroughs in Artificial General Intelligence (AGI) and scalable, production-ready engineering.
As a pioneer in next-generation technology, you will work on cutting-edge projects that set the standard for the industry. We offer a competitive compensation package, significant equity opportunities, and a culture that fosters innovation and technical excellence.
Core Objectives
- Architect robust, fault-tolerant AI systems capable of handling exabyte-scale data.
- Lead research initiatives in large language models (LLMs) and autonomous agents.
- Optimize neural networks for edge computing and quantum-adjacent hardware environments.
Responsibilities
- Design and implement scalable AI infrastructure for next-generation applications and services.
- Lead the research and development of Generative AI models, pushing the boundaries of current technology.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to deliver high-impact solutions.
- Mentor junior engineers and establish best practices for AI engineering within the organization.
- Stay ahead of the curve by researching emerging technologies in synthetic data and neural interfaces.
- Ensure system security, scalability, and performance optimization across all AI workloads.
- Define technical roadmaps and architectural strategies for the 2026 product lifecycle.
Qualifications
- Master’s degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Extensive experience (8+ years) in designing and deploying production-grade machine learning systems.
- Deep expertise in Python, PyTorch, TensorFlow, and modern GPU acceleration frameworks (CUDA, TensorRT).
- Proven track record of leading high-velocity engineering teams in a fast-paced startup environment.
- Strong understanding of distributed systems, cloud architecture (AWS/Azure/GCP), and MLOps pipelines.
- Excellent communication skills with the ability to translate complex technical concepts for diverse stakeholders.
- Familiarity with ethical AI principles and bias mitigation in large datasets.