Job Description
We are building the infrastructure for the year 2026. Nexus Future Systems is seeking a visionary Senior AI Architect to lead the development of our next-generation Generative AI platforms. You will be at the forefront of defining the AI landscape for the next decade, working on scalable, autonomous systems that redefine human-machine interaction.
In this role, you will bridge the gap between theoretical research and production-grade engineering, ensuring our AI capabilities are robust, ethical, and ready for the demands of a rapidly evolving digital ecosystem.
Responsibilities
- Lead the 2026 AI Roadmap: Define and execute the technical strategy for our agentic AI systems and Large Language Models (LLMs) with a focus on future-proof scalability.
- Architect High-Performance Systems: Design and optimize deep learning inference pipelines to handle millions of concurrent requests with sub-millisecond latency.
- Research & Innovation: Experiment with cutting-edge architectures (e.g., Mixture of Experts, Sparse Transformers) to push the boundaries of model efficiency.
- Model Optimization: Implement quantization, pruning, and distillation techniques to deploy massive models on edge devices and cloud infrastructure.
- Cross-Functional Leadership: Collaborate with product managers, data scientists, and security teams to align technical solutions with business objectives.
- Mentorship: Guide a team of junior engineers and researchers, fostering a culture of continuous learning and technical excellence.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Machine Learning, or a related technical field.
- Experience: 5+ years of professional experience in AI/ML engineering, with at least 2 years in a leadership or architect role.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, or JAX; deep understanding of CUDA and GPU optimization.
- Domain Knowledge: Extensive experience with Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Cloud Mastery: Strong expertise in cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Proven track record of solving complex engineering challenges in high-stakes environments.