Job Description
We are looking for a visionary Senior AI Architect to lead the 2026 Horizon Initiative, a cutting-edge research project dedicated to achieving Artificial General Intelligence (AGI). In this high-impact role, you will define the architectural blueprint for our proprietary neural networks, ensuring scalability, security, and ethical alignment as we prepare for the technological leap of 2026.
As a key member of our elite R&D team, you will bridge the gap between theoretical research and production-grade deployment. You will design the systems that will power the next generation of human-computer interaction, pushing the boundaries of deep learning and predictive modeling.
Responsibilities
- Architect and implement scalable, high-performance machine learning pipelines for the 2026 Horizon Initiative.
- Lead the research and development of advanced Natural Language Processing (NLP) and Computer Vision models.
- Optimize existing algorithms to reduce latency and improve real-time inference speeds.
- Establish rigorous best practices for data governance, model monitoring, and version control.
- Mentor junior developers and data scientists, fostering a culture of innovation and technical excellence.
- Collaborate closely with product management and engineering teams to integrate AI solutions seamlessly.
- Ensure compliance with global AI ethics and safety standards.
Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
- 10+ years of professional experience in AI/ML engineering and software architecture.
- Expert proficiency in Python, TensorFlow, PyTorch, and scikit-learn.
- Proven track record of deploying large-scale ML models to production environments (AWS, GCP, or Azure).
- Strong understanding of distributed systems, cloud infrastructure, and containerization (Docker, Kubernetes).
- Experience with ethical AI frameworks and bias mitigation strategies.
- Exceptional problem-solving skills and the ability to thrive in fast-paced, ambiguous environments.