Job Description
We are pioneering the next era of human-computer interaction. Nexus Horizon Labs is seeking a visionary Lead AI Architect to define the roadmap for Artificial General Intelligence (AGI) and autonomous systems. If you are passionate about building the technologies that will define the 2026 landscape and beyond, this is your opportunity to lead from the front lines.
In this role, you will not just manage models; you will architect the neural infrastructure that powers our next-generation agents. You will work with world-class researchers and engineers to solve unsolved problems in reasoning, memory, and adaptability.
Why Join Us?
- Work on high-impact, long-term research projects with a competitive compensation package.
- Access to cutting-edge compute resources and a culture of radical transparency.
- Shape the ethical framework of future AI technologies.
Responsibilities
- Architect and implement scalable, fault-tolerant AI infrastructure for large-scale model training and inference.
- Lead the research and development of next-generation multi-modal learning algorithms focused on long-term reasoning.
- Define the technical vision for AGI evolution, ensuring alignment with company product goals and ethical standards.
- Optimize deep learning pipelines to reduce latency and improve throughput for real-time applications.
- Mentor and guide a team of senior machine learning engineers and data scientists.
- Collaborate with product teams to translate theoretical research into deployable, production-ready features.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- 10+ years of experience in software engineering and machine learning, with at least 5 years in a leadership role.
- Deep expertise in Deep Learning frameworks (PyTorch, TensorFlow, JAX) and distributed computing (Ray, Kubernetes).
- Proven track record of publishing in top-tier conferences (NeurIPS, ICML, ICLR) or shipping complex production systems.
- Strong understanding of Large Language Models (LLMs), Transformers, and Reinforcement Learning from Human Feedback (RLHF).
- Experience with hardware acceleration (TPU/GPU clusters) and optimization techniques.