Job Description
Are you ready to architect the technology that defines the next decade? Nexus Core Systems is pioneering the 2026 roadmap, focusing on post-silicon computing and neuromorphic intelligence. We are seeking a visionary Senior AI Architect to lead the development of scalable, high-performance neural networks that will power the next generation of autonomous systems.
In this role, you won't just optimize existing models; you will design the infrastructure for the future. You will work at the intersection of hardware and software, pushing the boundaries of what's possible in real-time processing and generative AI. Join us in building the foundational technologies for a smarter, more connected world.
Why Join Us?
- Impactful Work: Directly influence the core architecture of our flagship 2026 products.
- Global Leadership: Collaborate with top-tier researchers and engineers globally.
- Future-Proof Career: Work on bleeding-edge technologies that define the industry standard.
Responsibilities
- Design and deploy advanced neural network architectures optimized for edge devices and cloud infrastructure.
- Lead the research and implementation of neuromorphic computing techniques for low-latency processing.
- Collaborate with hardware engineers to optimize data flow and memory management for AI workloads.
- Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Define technical roadmaps and best practices for scalable AI model training and inference.
- Conduct rigorous testing to ensure system robustness, security, and ethical AI compliance.
Qualifications
- PhD or Master's degree in Computer Science, Electrical Engineering, or a related quantitative field.
- Minimum of 7 years of experience in AI/ML engineering, with at least 3 years in a lead architecture role.
- Deep expertise in Python, PyTorch, TensorFlow, and CUDA programming.
- Proven track record of deploying large-scale machine learning models in production environments.
- Experience with distributed computing frameworks (Kubernetes, Apache Spark) and cloud platforms (AWS, GCP).
- Strong understanding of linear algebra, probability theory, and optimization algorithms.