Job Description
We are seeking a visionary Lead AI Architect to spearhead our Project 2026 initiative, a groundbreaking leap in autonomous neural network systems. At Aether Dynamics, we are not just building software; we are architecting the future of intelligent infrastructure. This is a rare opportunity to operate at the intersection of theoretical computer science and practical engineering, defining the standards for next-generation artificial general intelligence.
Why Join Us?
• Work on high-impact, cutting-edge technology that defines the industry roadmap for 2026.
• Collaborate with a world-class team of PhDs, cryptographers, and systems engineers.
• Competitive equity package and top-tier compensation.
Responsibilities
- Architect the 2026 Core: Design and implement the foundational architecture for our next-generation distributed AI model, ensuring scalability and fault tolerance.
- Performance Optimization: Lead efforts in reducing inference latency and improving training throughput by 50% using advanced quantization and pruning techniques.
- R&D Leadership: Conduct deep research into novel transformer architectures and reinforcement learning paradigms to push the boundaries of AI capability.
- System Integration: Bridge the gap between theoretical research and production deployment, integrating 2026 models into real-world high-frequency trading and logistics systems.
- Mentorship: Guide a team of senior engineers and researchers, fostering a culture of innovation and technical excellence.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, or a related technical field with a focus on AI/ML.
- Experience: 7+ years of professional experience in Machine Learning Engineering, with at least 3 years in a Lead or Architect role.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and C++ for high-performance computing.
- Specialized Knowledge: Deep understanding of Large Language Models (LLMs), Diffusion models, and federated learning.
- Problem Solving: Demonstrated ability to tackle ambiguous, high-complexity problems and deliver robust, scalable solutions under tight deadlines.