Job Description
Shape the Future of Intelligence
Are you ready to architect the systems that will define the year 2026 and beyond? Nexus Horizon Labs is seeking a visionary Senior AI Architect to lead our next-generation autonomous intelligence research division. In this role, you will not just write code; you will engineer the cognitive frameworks that bridge human intent and machine execution in a post-silicon era.
We are looking for a pioneer who thrives on ambiguity and is obsessed with the ethical and technical advancement of Artificial General Intelligence (AGI). Join us in building the infrastructure that powers the world of 2026.
Why Join Us?
- Work on cutting-edge projects that define the trajectory of global technology.
- Competitive compensation package with equity options.
- Flexible remote-first culture with premium in-office amenities in SF.
Responsibilities
- Architect Next-Gen Systems: Design and implement scalable, robust neural architectures for autonomous agents and generative AI models capable of reasoning in complex, multi-modal environments.
- Lead Research Initiatives: Spearhead research in Reinforcement Learning, Human-AI Alignment, and the integration of Quantum computing principles into classical ML pipelines.
- Model Optimization: Reduce inference latency and increase model accuracy by 40%+ using advanced quantization, pruning, and distributed training techniques.
- Ethical AI Governance: Establish frameworks to ensure AI outputs are unbiased, safe, and compliant with upcoming regulatory standards for autonomous systems.
- Technical Mentorship: Guide a team of top-tier ML engineers and researchers in best practices for scalable system design and production deployment.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field from a top-tier institution.
- Experience: 7+ years of professional experience in deep learning, with at least 3 years in a leadership or senior architecture role on large-scale systems.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and C++ for high-performance computing.
- Domain Knowledge: Deep understanding of Large Language Models (LLMs), Transformers, and multimodal architectures; experience with RAG (Retrieval-Augmented Generation) is highly preferred.
- Problem Solving: Demonstrated ability to solve complex, unstructured problems in high-stakes environments with a focus on long-term scalability.