Job Description
Are you ready to engineer the intelligence of tomorrow? Horizon 2026 Systems is looking for a world-class Senior AI Architect to lead the development of next-generation generative models. As we bridge the gap between theoretical research and real-world application, we need a visionary who can navigate the complexities of large-scale machine learning systems.
In this role, you will define the technical roadmap for our flagship AI products, optimizing neural architectures for unprecedented efficiency and accuracy. You will work in a collaborative environment with top-tier researchers and engineers, pushing the boundaries of what is possible in 2026 and beyond.
Responsibilities
- Model Development: Design, train, and fine-tune cutting-edge Large Language Models (LLMs) and computer vision systems using PyTorch and TensorFlow.
- System Architecture: Architect scalable MLOps pipelines to ensure reliable model deployment, monitoring, and retraining strategies.
- Performance Optimization: Implement techniques such as quantization, pruning, and distillation to reduce inference latency and cost.
- Research Integration: Translate the latest academic research papers into production-ready code and frameworks.
- Team Leadership: Mentor junior engineers and data scientists, conducting code reviews, and fostering a culture of technical excellence.
- Problem Solving: Troubleshoot complex edge cases and data inconsistencies to improve model robustness and fairness.
Qualifications
- Education: MS or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 5+ years of professional experience in machine learning engineering, with at least 2 years leading model deployment projects.
- Technical Skills: Deep proficiency in Python, PyTorch, and modern deep learning frameworks.
- LLM Expertise: Proven experience working with Transformers, BERT, GPT architectures, or similar NLP models.
- Infrastructure: Experience with cloud platforms (AWS/GCP/Azure) and containerization tools (Docker, Kubernetes).
- Mathematics: Strong understanding of linear algebra, calculus, and probability theory.