Job Description
We are seeking a visionary 2026 Neural Systems Architect to pioneer the next generation of synthetic intelligence infrastructure. At Aether Dynamics, we are building the foundational architecture for the post-silicon era. You will not just be writing code; you will be designing the cognitive frameworks that will power autonomous systems, quantum-augmented decision making, and next-gen user interfaces. If you are driven by the challenge of engineering at the edge of tomorrow, this is your opportunity to define the future.
Why Join Us?
We are a top-tier R&D lab pushing the boundaries of what is possible. Our team works with state-of-the-art hardware and cutting-edge algorithms to create systems that learn, adapt, and evolve. You will receive a competitive package, equity options, and the autonomy to innovate without bureaucratic friction.
Responsibilities
- Architect and design scalable neural pathways for 2026 flagship applications, focusing on low-latency processing and high-throughput data ingestion.
- Lead the integration of quantum computing elements into classical machine learning pipelines to solve complex optimization problems.
- Develop robust error-correction and fault-tolerance protocols for autonomous distributed networks.
- Collaborate with cross-functional teams of data scientists, hardware engineers, and UX designers to translate theoretical AI models into production-ready systems.
- Define technical roadmaps for the evolution of our core AI engine, ensuring alignment with long-term product goals.
- Conduct rigorous code reviews and architectural audits to maintain the highest standards of security and efficiency.
Qualifications
- Master’s or Ph.D. in Computer Science, Computational Neuroscience, or a related field with a focus on AI/ML.
- Minimum of 8 years of professional experience in system architecture, with at least 3 years specifically in deep learning infrastructure.
- Deep expertise in Python, C++, and Rust, with a proven track record of optimizing performance-critical codebases.
- Experience deploying and scaling models on cloud infrastructure (AWS, GCP) and edge devices.
- Strong understanding of generative adversarial networks (GANs), transformers, and reinforcement learning paradigms.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to diverse stakeholders.