Job Description
We are on the precipice of a technological singularity. Nexus Horizon AI is seeking a visionary Future AI Architect to lead our research into Artificial General Intelligence (AGI) and autonomous systems. In this pivotal role, you will not just build models for today; you will architect the intelligent frameworks for 2026 and beyond.
Your work will define the ethical standards, computational efficiency, and scalability of the next generation of AI agents. If you are obsessed with pushing the boundaries of neural architectures and predictive analytics, this is your mission.
Why Join Us?
- Next-Gen R&D: Work on cutting-edge projects in Generative Adversarial Networks (GANs) and Large Language Models (LLMs).
- Global Impact: Shape the future of automation and human-machine collaboration.
- Top-Tier Talent: Collaborate with world-class engineers and researchers from top universities.
Key Responsibilities:
- Design and implement scalable neural network architectures for 2026-era computing paradigms.
- Lead research initiatives in autonomous decision-making and reinforcement learning.
- Optimize AI models for edge computing and real-time inference.
- Collaborate with product teams to integrate predictive AI into consumer and enterprise solutions.
- Conduct rigorous testing of AI safety protocols and bias mitigation strategies.
- Publish high-impact research papers and patents in the field of computational intelligence.
Qualifications:
- Ph.D. or Master’s degree in Computer Science, Mathematics, or a related quantitative field.
- 7+ years of experience in Machine Learning, Deep Learning, or AI Engineering.
- Proficiency in Python, PyTorch, and TensorFlow.
- Experience with Large Language Models (LLMs), Transformers, and Vector Databases.
- Strong understanding of distributed systems and cloud infrastructure (AWS/GCP).
- Track record of deploying production-grade AI models at scale.
Responsibilities
- Design and implement scalable neural network architectures for 2026-era computing paradigms.
- Lead research initiatives in autonomous decision-making and reinforcement learning.
- Optimize AI models for edge computing and real-time inference.
- Collaborate with product teams to integrate predictive AI into consumer and enterprise solutions.
- Conduct rigorous testing of AI safety protocols and bias mitigation strategies.
- Publish high-impact research papers and patents in the field of computational intelligence.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Mathematics, or a related quantitative field.
- 7+ years of experience in Machine Learning, Deep Learning, or AI Engineering.
- Proficiency in Python, PyTorch, and TensorFlow.
- Experience with Large Language Models (LLMs), Transformers, and Vector Databases.
- Strong understanding of distributed systems and cloud infrastructure (AWS/GCP).
- Track record of deploying production-grade AI models at scale.