Job Description
Are you ready to architect the future of Artificial General Intelligence (AGI)?
At Quantum Horizon Systems, we are on a mission to redefine the technological landscape by 2026. We are seeking a visionary Senior AI Architect to lead our cutting-edge Generative AI division. You won't just be writing code; you will architect the neural pathways that power the next generation of autonomous agents and multimodal systems.
In this role, you will bridge the gap between theoretical machine learning breakthroughs and scalable, real-world deployment. If you thrive in ambiguity and are passionate about the future of human-machine interaction, we want to hear from you.
Why join us? We offer top-tier equity, a state-of-the-art compute cluster, and the autonomy to push the boundaries of what AI can achieve.
Responsibilities
- Design and implement scalable Generative AI models and LLM orchestration frameworks for enterprise deployment.
- Lead the architecture of Autonomous Agent Systems capable of complex decision-making and multi-step reasoning.
- Optimize inference latency and model accuracy through advanced quantization and pruning techniques.
- Collaborate with cross-functional teams to integrate AI solutions into legacy systems, ensuring seamless interoperability.
- Establish best practices for Ethical AI, ensuring bias mitigation and safety protocols in large-scale models.
- Pioneering research into next-gen architectures, such as State Space Models (SSM) and Neuro-symbolic AI.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related technical field.
- 5+ years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Proficiency in Python, PyTorch, TensorFlow, and modern GPU acceleration libraries (CUDA, cuDNN).
- Deep understanding of Large Language Models (LLMs), fine-tuning methodologies, and Retrieval-Augmented Generation (RAG).
- Experience with vector databases (e.g., Pinecone, Weaviate) and high-throughput API design.
- Strong problem-solving skills with a focus on mathematical rigor and algorithmic efficiency.