Job Description
Architect the Future of Intelligence.
NeoHorizon Corp is at the forefront of the AI revolution. We are looking for a visionary Senior AI Architect to lead our elite Project 2026 initiative. This role is critical in defining the next generation of scalable, ethical, and high-performance machine learning systems.
As a Senior Architect, you won't just write code; you will shape the architectural backbone of our upcoming products. You will bridge the gap between theoretical research and production engineering, ensuring our solutions are robust, efficient, and ready for global deployment.
What You'll Do:
- Design and implement scalable machine learning pipelines and distributed computing architectures.
- Lead technical strategy for Project 2026, overseeing model training, fine-tuning, and deployment.
- Collaborate with cross-functional teams to integrate AI models into consumer and enterprise products.
- Optimize model performance for low-latency inference and high-throughput processing.
- Mentor a team of talented engineers, conducting code reviews and fostering a culture of innovation.
- Ensure system reliability, security, and compliance with industry standards.
Responsibilities
- Design and implement scalable machine learning pipelines and distributed computing architectures.
- Lead technical strategy for Project 2026, overseeing model training, fine-tuning, and deployment.
- Collaborate with cross-functional teams to integrate AI models into consumer and enterprise products.
- Optimize model performance for low-latency inference and high-throughput processing.
- Mentor a team of talented engineers, conducting code reviews and fostering a culture of innovation.
- Ensure system reliability, security, and compliance with industry standards.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related technical field.
- 5+ years of experience in machine learning engineering, deep learning, or AI research.
- Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
- Strong understanding of distributed systems, cloud platforms (AWS/GCP), and containerization (Docker/Kubernetes).
- Experience with Large Language Models (LLMs) and RAG (Retrieval-Augmented Generation) architectures.
- Proven ability to translate complex research papers into production-ready software.