Job Description
Are you ready to architect the future of intelligence? Nexus 2026 is seeking a visionary Senior Generative AI Architect to lead our cutting-edge research division. In this pivotal role, you will define the technical strategy for our next-generation large language models and multimodal systems, pushing the boundaries of what AI can achieve in real-world applications.
We are looking for a thought leader who thrives in ambiguity and possesses the technical prowess to build scalable, robust, and ethical AI solutions. You will work closely with product leaders and engineering teams to translate complex research concepts into production-ready systems that impact millions of users globally.
Responsibilities
- Lead Technical Vision: Define the architectural roadmap for Generative AI systems, focusing on scalability, latency reduction, and cost efficiency.
- Model Development: Design and optimize Large Language Models (LLMs) and diffusion models using state-of-the-art frameworks like PyTorch and TensorFlow.
- System Optimization: Implement high-performance inference pipelines and fine-tuning strategies to ensure models run efficiently on edge devices and cloud infrastructure.
- R&D Collaboration: Partner with world-class researchers to explore novel AI paradigms, including Reinforcement Learning from Human Feedback (RLHF) and Constitutional AI.
- Mentorship: Guide a team of junior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Ethical AI: Establish and enforce guidelines to ensure AI outputs are fair, unbiased, and safe for public deployment.
Qualifications
- Education: M.S. or Ph.D. in Computer Science, Machine Learning, Mathematics, or a related technical field.
- Experience: 5+ years of professional experience in machine learning engineering, with a focus on NLP or generative models.
- Technical Skills: Proficiency in Python, C++, and deep learning frameworks (PyTorch, JAX, TensorFlow).
- Architecture: Strong understanding of distributed systems, cloud architecture (AWS/GCP/Azure), and MLOps practices.
- Soft Skills: Excellent communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
- Creativity: A proven track record of innovating solutions to complex, open-ended problems.