Job Description
The Future is Here. Are you ready to architect the intelligent systems that will define the 2026 era? Nexus Horizon AI is seeking a visionary Senior AI Architect to lead our next-generation neural network initiatives. You won't just be maintaining legacy systems; you will be building the infrastructure for the autonomous, predictive, and ethical AI of tomorrow.
In this pivotal role, you will bridge the gap between theoretical machine learning models and scalable, high-performance production systems. We are looking for a thought leader who is obsessed with scalability, security, and the ethical implications of advanced artificial intelligence.
Why Join Us?
We are a venture-backed startup redefining the boundaries of Generative AI and predictive analytics. You will work with state-of-the-art technology, mentor a world-class engineering team, and have a direct impact on the future of technology.
Responsibilities
- Design Scalable Architectures: Architect and implement robust, scalable AI systems capable of processing petabytes of data in real-time.
- Lead GenAI Integration: Spearhead the integration and optimization of Large Language Models (LLMs) and generative diffusion models into core products.
- Quantum Readiness: Develop data structures and algorithms that are optimized for future quantum computing environments.
- AI Ethics & Compliance: Establish frameworks to ensure AI transparency, fairness, and adherence to global data privacy regulations.
- System Optimization: Fine-tune deep learning models for edge computing and high-latency environments.
- Tech Leadership: Mentor junior engineers and define technical best practices for the engineering department.
Qualifications
- Experience: 5+ years of professional experience in AI/ML engineering, with at least 2 years in a senior architecture or lead role.
- Core Tech Stack: Proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (Kubernetes, Docker).
- Deep Learning: Strong background in Deep Neural Networks, NLP, and Computer Vision.
- Education: Master’s degree in Computer Science, Mathematics, or a related field (PhD preferred).
- Problem Solving: Proven track record of solving complex engineering challenges and optimizing system performance.
- Communication: Excellent ability to communicate complex technical concepts to non-technical stakeholders.