Job Description
Shape the Future of Intelligence
We are Aether Dynamics, a pioneer in the next generation of Artificial General Intelligence. We are looking for a visionary Senior AI Architect to lead the development of our proprietary LLM infrastructure. In this role, you won't just write code; you will architect the cognitive backbone for the year 2026 and beyond. Join us in building systems that learn, reason, and interact in ways previously thought impossible.
Why Join Us?
- Work on cutting-edge Autonomous Agents and Reasoning Models.
- Competitive compensation package including equity.
- Top-tier engineering environment with state-of-the-art compute.
- Flexible remote-first culture with hubs in SF and NYC.
Responsibilities
- Architecting Scalable LLM Systems: Design and implement robust, high-throughput inference pipelines for large language models using PyTorch and Rust.
- Model Optimization: Apply techniques such as quantization, pruning, and knowledge distillation to deploy massive models on edge devices without compromising quality.
- RAG & Vector Database Engineering: Build advanced Retrieval-Augmented Generation systems to enhance factual accuracy and reduce hallucinations.
- Research Integration: Translate academic research papers into production-ready code, bridging the gap between theory and real-world application.
- Multimodal Processing: Lead the integration of vision and audio inputs into our core reasoning engines.
- System Evaluation: Establish rigorous benchmarks and evaluation frameworks to measure model performance against industry standards.
Qualifications
- Education: MS or PhD in Computer Science, Mathematics, or a related field with a focus on Machine Learning.
- Experience: 5+ years of professional experience building production AI systems, with deep expertise in Transformers and attention mechanisms.
- Technical Stack: Proficiency in Python, C++, and CUDA programming; extensive experience with frameworks like Hugging Face, LangChain, and TensorFlow.
- Algorithmic Mastery: Strong understanding of optimization algorithms, neural architecture search, and reinforcement learning.
- Problem Solving: Ability to troubleshoot complex distributed system failures and optimize for low-latency, high-concurrency environments.
- Communication: Excellent technical writing skills and the ability to present complex AI concepts to non-technical stakeholders.