Job Description
Shape the Future of Intelligence.
Quantum Horizon Technologies is pioneering the next generation of Artificial General Intelligence (AGI). We are seeking a visionary Senior AI Architect to lead our research division and build the infrastructural backbone for our 2026 strategic roadmap. If you are passionate about solving unsolved problems in deep learning, neural scaling, and ethical AI, this is your chance to define the future.
As a Senior AI Architect, you will not just write code; you will design the cognitive architectures of tomorrow. You will bridge the gap between theoretical research and scalable production systems, ensuring our models are robust, efficient, and responsible.
Why Join Us?
- Work on projects that directly impact the trajectory of human-computer interaction.
- Competitive compensation and equity package.
- Access to top-tier computing resources and research libraries.
Responsibilities
- Architect and implement scalable AI/ML infrastructure capable of handling petabyte-scale neural network training.
- Lead the research and development of proprietary Generative AI models and transformer architectures.
- Define the technical vision for our 2026 roadmap, including predictive analytics and autonomous agent systems.
- Optimize model inference latency and resource utilization in high-volume production environments.
- Collaborate with security experts to implement robust AI safety and governance frameworks.
- Mentor a team of elite Data Scientists and ML Engineers to foster a culture of innovation.
- Establish MLOps pipelines to streamline model deployment and monitoring.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- 7+ years of experience in Machine Learning Engineering, with at least 3 years in a senior architectural or lead role.
- Deep expertise in Python, PyTorch, TensorFlow, and distributed computing (Kubernetes, Ray, Spark).
- Proven experience deploying Large Language Models (LLMs) and Generative AI at scale.
- Strong understanding of cloud architecture (AWS, GCP, or Azure) and serverless computing.
- Experience with Reinforcement Learning and Multi-Agent Systems.
- Excellent communication skills and the ability to translate complex technical concepts for stakeholders.