Job Description
Are you ready to build the world of 2026?
At Aether Dynamics, we aren't just predicting the future; we are architecting it. We are the pioneers behind the world's most advanced neural interface systems and autonomous quantum computation frameworks. As we accelerate towards our 2026 release targets, we need a visionary Senior AI Architect to lead the charge in designing scalable, hyper-efficient intelligence systems.
In this pivotal role, you will bridge the gap between theoretical machine learning breakthroughs and practical, deployable software solutions. You will work on projects that redefine human-computer interaction and set the standard for the next decade of technology.
Why join us?
- Impact: Directly influence the core architecture of products used by millions.
- Innovation: Work with state-of-the-art Quantum AI and Neural Processing Units.
- Equity: Competitive RSU package tied to the success of our 2026 roadmap.
- Flexibility: Hybrid work model supporting both home and office collaboration.
If you possess the foresight and technical prowess to lead the next generation of AI, we want to meet you.
Responsibilities
- Architect and implement scalable machine learning pipelines for real-time data processing and prediction models.
- Lead the research and integration of cutting-edge Neural Network architectures (Transformers, GANs, Reinforcement Learning).
- Collaborate with cross-functional teams of quantum physicists and hardware engineers to optimize AI model inference on novel hardware.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.
- Define technical roadmaps and best practices for the AI engineering department leading up to the 2026 launch.
- Conduct rigorous code reviews and performance optimization to ensure system reliability and speed.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field (PhD preferred).
- Minimum of 5+ years of professional experience in designing and deploying large-scale machine learning systems.
- Deep expertise in Python, C++, and modern frameworks such as TensorFlow, PyTorch, or JAX.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Strong background in statistics, linear algebra, and optimization algorithms.
- Demonstrated ability to work in fast-paced, agile environments and manage complex technical projects.