Job Description
Join Horizon 2026, the pioneering force behind the next generation of autonomous systems. We are not just building for today; we are architecting the technological infrastructure that will define the future. We are seeking a visionary Principal AI Architect to lead our cutting-edge research and development division.
In this pivotal role, you will bridge the gap between theoretical deep learning and real-world application. You will guide a team of elite engineers in deploying generative models and reinforcement learning systems capable of operating in complex, dynamic environments. If you are passionate about pushing the boundaries of what is possible in artificial intelligence and want to leave a legacy in the year 2026 and beyond, we want to meet you.
Why Join Horizon 2026?
- Impactful Work: Directly influence the roadmap of our flagship AI products.
- Future-Proofing: Work with bleeding-edge technologies including Transformer models and quantum-inspired algorithms.
- Elite Team: Collaborate with world-class researchers and engineers.
- Competitive Compensation: Industry-leading salary and equity packages.
Responsibilities
- Architect and design scalable, high-performance AI systems and machine learning pipelines for production deployment.
- Lead the research and implementation of novel deep learning architectures, specifically focusing on NLP and Computer Vision.
- Define technical strategies and mentor senior engineers and data scientists on best practices in MLOps and model training.
- Conduct rigorous performance testing and optimization to ensure low-latency, high-throughput inference.
- Collaborate with cross-functional product teams to translate business requirements into robust technical solutions.
- Stay abreast of the latest advancements in AI research and integrate relevant breakthroughs into the product roadmap.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence.
- 10+ years of professional experience in software engineering, with at least 5 years specifically in AI/ML architecture.
- Deep expertise in Python, PyTorch, TensorFlow, and C++.
- Proven track record of deploying large-scale machine learning models in production environments.
- Strong understanding of distributed systems, cloud infrastructure (AWS/GCP), and containerization (Docker/Kubernetes).
- Exceptional problem-solving skills and the ability to navigate ambiguity in fast-paced environments.