Job Description
Architect the Future of Intelligence
We are looking for a visionary Senior AI/ML Architect to join Nexus Horizon AI. In 2026, the boundary between biological and digital intelligence is dissolving. We are building the foundational systems that will power the next generation of autonomous agents, neural interfaces, and generative ecosystems. If you are driven by the challenge of defining what comes next, this is your stage.
Why Nexus Horizon?
We are a pioneer in next-gen AI infrastructure. We don't just build models; we engineer the reality they inhabit. As we expand our 2026 roadmap, we need a technical leader who can translate abstract neural concepts into scalable, production-ready code.
What You'll Do
As a Senior Architect, you will define the technical DNA of our future products. Your work will directly influence how humanity interacts with autonomous systems.
Responsibilities
Core Responsibilities
- Design Scalable Neural Architectures: Lead the design and implementation of advanced deep learning models and large-scale neural networks optimized for 2026 computational demands.
- Future-Proof Infrastructure: Architect cloud-native ML pipelines that leverage edge computing and decentralized data structures to ensure resilience and speed.
- Model Optimization & Efficiency: Spearhead research into model pruning, quantization, and hardware acceleration (TPU/GPU) to reduce inference costs.
- Technical Mentorship: Cultivate a high-performance engineering culture, mentoring junior architects and data scientists in best practices for AI safety and ethics.
- Roadmap Strategy: Collaborate with product and research teams to define technical roadmaps that align with the 2026 vision of ubiquitous AI.
- System Integration: Oversee the integration of AI systems into broader enterprise ecosystems, ensuring seamless interoperability.
Qualifications
Requirements
- Education: Master’s degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Experience: 7+ years of experience in software engineering with a focus on Machine Learning, Deep Learning, or Applied AI.
- Technical Proficiency: Expert-level knowledge in Python, PyTorch, TensorFlow, and distributed computing frameworks (Kubernetes, Docker).
- Research Background: Proven track record of publishing in top-tier AI conferences (NeurIPS, ICML, ICLR) or leading internal R&D initiatives.
- Problem Solving: Exceptional ability to tackle ambiguous, novel problems common in cutting-edge AI research.
- Communication: Excellent technical writing and presentation skills, capable of bridging the gap between researchers and engineers.
- Location: Must be willing to work in our San Francisco headquarters or a hybrid model.