Job Description
We are on the precipice of a new era in cognitive computing. Horizon Dynamics is seeking a visionary Senior AI Architect to spearhead Project 2026, our ambitious initiative to develop next-generation predictive artificial intelligence systems designed for autonomous infrastructure management.
In this pivotal role, you will not just write code; you will define the architectural blueprints for the future of intelligent automation. You will work at the intersection of deep learning, distributed systems, and real-time data processing to build models that are not only accurate but ethically robust and scalable.
Join a team of world-class engineers and researchers dedicated to pushing the boundaries of what is possible in 2026 and beyond.
Responsibilities
- Lead the architectural design and implementation of complex deep learning pipelines for Project 2026, focusing on reinforcement learning and predictive analytics.
- Collaborate with data scientists and software engineers to optimize model performance, latency, and resource efficiency.
- Establish best practices for MLOps, ensuring seamless deployment and monitoring of AI models in production environments.
- Research and evaluate emerging technologies in generative AI and quantum-inspired algorithms to maintain a competitive edge.
- Drive technical decision-making regarding infrastructure scaling, security, and compliance in high-stakes environments.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related field, with a focus on Artificial Intelligence or Machine Learning.
- Minimum of 8 years of experience in designing scalable AI/ML systems, preferably in a senior or lead capacity.
- Deep expertise in Python, PyTorch, TensorFlow, and C++.
- Strong understanding of Large Language Models (LLMs), transformer architectures, and fine-tuning methodologies.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Exceptional problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.