Job Description
We are seeking a visionary Principal AI Architect to spearhead our flagship initiative, Project 2026. As the industry accelerates toward the next decade of intelligent automation, Apex Horizon Systems is building the neural infrastructure for the future. You will be responsible for architecting scalable, high-performance machine learning systems that redefine industry standards.
In this high-impact role, you will bridge the gap between theoretical research and production-grade engineering. You will lead a world-class team of data scientists and engineers, ensuring our proprietary models are not only accurate but also ethically sound and secure. If you are passionate about pushing the boundaries of generative AI and predictive analytics, this is your opportunity to shape the digital landscape of 2026.
Responsibilities
- Architect and deploy end-to-end AI solutions for Project 2026, focusing on large language models and predictive analytics.
- Lead the technical strategy for model training pipelines, optimizing for speed, accuracy, and cost-efficiency.
- Mentor and coach senior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Collaborate with cross-functional teams to integrate AI capabilities into core product ecosystems.
- Ensure compliance with data privacy regulations and implement robust security measures for sensitive data.
- Conduct deep-dive research into emerging AI methodologies to maintain a competitive edge.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field (PhD preferred).
- 10+ years of experience in software engineering, with at least 5 years focused on Artificial Intelligence and Machine Learning.
- Deep expertise in Python, PyTorch, TensorFlow, and distributed computing frameworks.
- Proven track record of leading engineering teams and delivering complex projects on time.
- Strong understanding of NLP, Computer Vision, or Reinforcement Learning (Project 2026 specific focus required).
- Experience with cloud infrastructure (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).