Job Description
Are you ready to shape the intelligence of tomorrow? Aether Systems is on the hunt for a visionary Senior AI Architect to spearhead our breakthrough projects targeting the 2026 technological horizon. We are building the foundational layers of next-generation Artificial General Intelligence (AGI) and are looking for a leader who can navigate the complexities of large-scale neural architectures with precision and ethical foresight.
In this pivotal role, you will bridge the gap between theoretical research and production-grade deployment. You will architect systems that are not only powerful but scalable and safe for global implementation. Join us in defining the roadmap for 2026 and beyond, working with state-of-the-art hardware and cutting-edge algorithms.
In this pivotal role, you will bridge the gap between theoretical research and production-grade deployment. You will architect systems that are not only powerful but scalable and safe for global implementation. Join us in defining the roadmap for 2026 and beyond, working with state-of-the-art hardware and cutting-edge algorithms.
Responsibilities
- Design and implement scalable, high-performance neural network architectures tailored for the 2026 AI landscape.
- Lead the research and development of advanced Natural Language Processing (NLP) and multimodal models.
- Optimize inference pipelines to ensure real-time performance on distributed GPU clusters.
- Establish best practices for model training, validation, and safety alignment to prevent bias and ensure ethical deployment.
- Collaborate with cross-functional teams including data scientists, engineers, and product managers to translate complex research into viable products.
- Mentor junior engineers and researchers, fostering a culture of innovation and technical excellence.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence.
- Proven experience (7+ years) building and deploying large-scale machine learning systems in a production environment.
- Deep expertise in deep learning frameworks such as PyTorch, TensorFlow, or JAX.
- Strong proficiency in Python and C++.
- Experience with MLOps tools, cloud infrastructure (AWS/GCP/Azure), and containerization (Docker/Kubernetes).
- Track record of publishing in top-tier AI conferences (NeurIPS, ICML, ICLR) or significant contributions to open-source AI projects.