Job Description
We are at the precipice of a technological singularity. Nexus Horizon Labs is seeking a visionary Lead AI Architect to spearhead our research into Artificial General Intelligence (AGI) and define the technological roadmap for 2026 and beyond.
In this role, you won't just maintain existing models; you will architect the foundational systems that power the next generation of sentient AI. You will bridge the gap between theoretical machine learning and scalable production infrastructure, ensuring our solutions are not only powerful but ethically sound and future-proof.
If you are a pioneer who thrives on solving unsolved problems and wants to leave a legacy in the history of AI, we want to meet you.
Responsibilities
- Architect Core Systems: Design and implement scalable, high-performance neural architectures for large-scale multi-modal models.
- Lead Research Strategy: Define the technical vision for 2026, exploring cutting-edge areas such as emergent reasoning, self-supervised learning, and memory-augmented networks.
- Optimize Inference: Lead initiatives to reduce latency and improve throughput for real-time AI applications in high-demand environments.
- Cross-Functional Leadership: Mentor a team of senior ML engineers and data scientists, fostering a culture of innovation and technical excellence.
- Ethical AI Governance: Establish frameworks for bias mitigation and ensure alignment with global AI safety standards.
- Technical Evangelism: Collaborate with product teams to translate complex AI capabilities into user-centric solutions.
Qualifications
- Education: PhD in Computer Science, Mathematics, or a related field, or equivalent practical experience.
- Experience: 8+ years of experience in Machine Learning, Deep Learning, or AI research, with at least 3 years in a leadership or architect role.
- Technical Mastery: Deep expertise in PyTorch, TensorFlow, or JAX, and proven experience training state-of-the-art Large Language Models (LLMs).
- Mathematical Foundation: Strong grasp of linear algebra, calculus, probability, and optimization theory.
- Problem Solving: Demonstrated ability to tackle novel, open-ended problems and drive innovation from concept to deployment.
- Communication: Exceptional ability to communicate complex technical concepts to both technical and non-technical stakeholders.