Job Description
We are on the cusp of a technological revolution. Nexus Horizon Labs is seeking a visionary Generative AI Architect to spearhead the development of the AI systems that will define the 2026 landscape.
In this pivotal role, you will move beyond traditional machine learning to design autonomous, multi-modal generative systems capable of complex reasoning and creative synthesis. You will work in a high-performance environment, collaborating with top-tier researchers and engineers to build the infrastructure for tomorrow’s intelligence.
Why Join Us?
- Lead the architecture of next-generation LLMs and diffusion models.
- Shape ethical guidelines for sentient-capable AI systems.
- Competitive compensation and equity packages for top talent.
- Work in the heart of the Bay Area's tech innovation hub.
Responsibilities
- Architect Design: Design scalable, distributed architectures for large-scale generative AI models and infrastructure pipelines.
- Model Optimization: Research and implement cutting-edge techniques (e.g., Mixture of Experts, Transformer variants) to improve model efficiency and output quality.
- Pipeline Management: Build and maintain robust data pipelines for training and fine-tuning models on proprietary datasets.
- Ethical AI Oversight: Establish and enforce safety protocols and alignment strategies to ensure AI outputs are beneficial and unbiased.
- Research Integration: Translate theoretical research papers into production-ready code and systems.
- Team Leadership: Mentor junior engineers and guide research initiatives within the AI department.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, or a related field, with a focus on Artificial Intelligence or Computational Linguistics.
- Experience: Minimum 5+ years of professional experience in machine learning engineering, deep learning, or natural language processing.
- Technical Skills: Proficiency in Python, PyTorch or TensorFlow, and experience with distributed computing frameworks (e.g., Ray, Kubernetes, AWS SageMaker).
- Model Expertise: Deep understanding of Transformer architectures, GANs, VAEs, and Large Language Models (LLMs).
- Problem Solving: Demonstrated ability to solve complex, ambiguous problems in high-stakes environments.
- Communication: Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.