Job Description
Are you ready to define the technology stack of 2026?
Nexus Horizon Labs is seeking a visionary Future AI Architect to lead our research into Generative AI, Autonomous Agents, and Quantum-Enhanced Machine Learning. As we prepare for the next era of artificial intelligence, we need a technical leader who can bridge the gap between theoretical research and scalable production systems.
In this role, you will be responsible for architecting the foundational models that will power our ecosystem five years from now. You will work closely with quantum computing researchers and data scientists to build a sustainable, ethical, and incredibly powerful AI infrastructure.
Why join us?
We offer top-tier compensation, equity packages, and the freedom to explore cutting-edge technologies without the bureaucratic red tape of traditional tech giants.
Responsibilities
- Architect the 2026 AI Roadmap: Design and implement the long-term technical strategy for our next-generation Large Language Models and multimodal agents.
- Model Optimization: Lead initiatives to optimize model inference speed and reduce latency using cutting-edge techniques like quantization and pruning.
- Ethical AI Governance: Establish and enforce strict safety guidelines and fairness protocols to ensure AI systems are robust and unbiased.
- Cross-Functional Leadership: Mentor a team of senior engineers and researchers, fostering a culture of innovation and continuous learning.
- R&D Integration: Collaborate with external partners and academic institutions to integrate novel research into our core product suite.
- Infrastructure Scaling: Oversee the migration of legacy systems to our next-gen, cloud-native AI infrastructure.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 7+ years of experience in software engineering, specifically within the Machine Learning/AI domain.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, and Hugging Face transformers.
- Research: Proven track record of publishing papers in top-tier AI conferences (NeurIPS, ICML, ACL) or leading open-source model development.
- System Design: Strong ability to design scalable distributed systems capable of handling petabytes of data.
- Leadership: Experience managing high-performing engineering teams and driving technical vision.