Job Description
We are on the precipice of a technological revolution, and we are looking for a visionary Lead AI Architect to help define the landscape of 2026. At Aether Dynamics, we don't just build software; we engineer the intelligence that will power the next decade. You will be at the helm of our cutting-edge research division, tasked with building the foundational models that will scale to billions of users.
If you are passionate about the future of Artificial General Intelligence (AGI), possess an insatiable curiosity, and thrive in high-stakes environments, we want to hear from you.
Why Join Us?
- Impactful Work: Your code will shape the core intelligence of our ecosystem.
- Future-Proofing: Focus on long-term scalability and ethical AI development.
- Elite Team: Collaborate with PhDs and industry veterans from top tech giants.
Responsibilities
- Architect Next-Gen Systems: Design and implement the core infrastructure for Large Language Models (LLMs) and multimodal AI systems targeting the 2026 deployment cycle.
- Research & Development: Lead experimental research in neural architecture search (NAS) and transformer optimization techniques.
- Model Training Pipelines: Oversee the end-to-end lifecycle of model training, from data ingestion to fine-tuning and deployment.
- Scalability Strategy: Ensure our AI infrastructure can handle exabyte-scale data processing with zero-latency inference.
- Ethical AI Governance: Establish frameworks for bias mitigation, transparency, and safety in automated decision-making systems.
- Team Leadership: Mentor a team of senior engineers and data scientists, fostering a culture of innovation and technical excellence.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field (PhD preferred).
- Experience: 7+ years of professional experience in AI/ML engineering, with at least 3 years in a leadership or architect role.
- Technical Stack: Deep expertise in PyTorch, TensorFlow, or JAX; proficiency in C++ for high-performance computing.
- Domain Knowledge: Proven track record of deploying successful AI products in production environments.
- Problem Solving: Demonstrated ability to solve complex, unstructured problems in stochastic systems.
- Communication: Exceptional ability to translate complex technical concepts into clear strategies for non-technical stakeholders.