Job Description
We are on a mission to define the future of intelligence. Nexus AI Labs is seeking a visionary Lead AI Architect (AGI Research Scientist) to spearhead our next-generation Artificial General Intelligence initiatives. In this high-impact role, you will design the neural architectures and algorithms that will power the next decade of technological advancement.
You will work in a fast-paced, elite research environment, collaborating with top-tier engineers and data scientists to bridge the gap between theoretical machine learning and practical, world-changing applications. If you are obsessed with pushing the boundaries of what is possible with deep learning and have a passion for ethical AI development, this is your opportunity to lead the charge.
Responsibilities
- Architect Next-Gen AI Systems: Design, prototype, and implement scalable neural architectures for AGI applications, including Large Language Models and multimodal agents.
- Drive Research Innovation: Lead high-level research initiatives to explore novel methodologies in self-supervised learning, reinforcement learning, and reasoning algorithms.
- Publish & Influence: Author peer-reviewed papers and technical blog posts to establish Nexus AI Labs as a thought leader in the AI community.
- Mentorship: Guide and mentor a team of junior researchers and machine learning engineers, fostering a culture of technical excellence and continuous learning.
- Collaboration: Partner with cross-functional teams (Product, Engineering, Ethics) to translate complex research into deployable, high-performance software solutions.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, Statistics, or a related field, with a focus on AI, Machine Learning, or Deep Learning.
- Experience: 8+ years of experience in software engineering and machine learning research, with at least 3 years in a lead or senior architect role.
- Technical Mastery: Deep expertise in PyTorch, TensorFlow, or JAX, with proven experience building large-scale transformer models or similar architectures.
- Programming: Proficiency in Python, C++, and distributed systems engineering.
- Problem Solving: Exceptional ability to tackle ambiguous problems and devise innovative solutions in complex environments.