Job Description
Welcome to the future of intelligence. Aether Dynamics is pioneering the next generation of autonomous systems, and we are looking for a visionary Senior Generative AI Architect to join our San Francisco headquarters.
In this pivotal role, you will architect and deploy large-scale generative models that define the technological landscape of 2026 and beyond. You will bridge the gap between theoretical research and production-grade applications, ensuring our AI solutions are scalable, ethical, and transformative.
Join a team of world-class engineers and researchers dedicated to pushing the boundaries of what is possible with Artificial Intelligence.
Why Join Us?
- Work on cutting-edge LLM and multimodal model research.
- Competitive compensation package including equity.
- Flexible remote/hybrid work options in the heart of Silicon Valley.
Responsibilities
- Model Architecture: Design and implement novel generative AI architectures (Transformers, Diffusion Models, GANs) optimized for high-throughput inference.
- Production Deployment: Lead the end-to-end deployment of ML models on cloud infrastructure (AWS/GCP/Azure), ensuring high availability and low latency.
- Optimization: Fine-tune and optimize existing models for specific enterprise use cases, improving accuracy and reducing computational costs.
- R&D Collaboration: Partner with our research team to translate academic breakthroughs into practical, commercial applications.
- MLOps: Establish robust MLOps pipelines for continuous training, evaluation, and monitoring of AI models.
- Ethical AI: Implement governance frameworks to ensure model fairness, transparency, and safety.
- Technical Leadership: Mentor junior engineers and conduct code reviews to maintain high engineering standards across the organization.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related technical field (PhD preferred).
- Experience: 5+ years of professional experience in machine learning engineering, with at least 2 years focused specifically on generative models or large language models.
- Programming: Expert-level proficiency in Python and C++. Deep understanding of PyTorch or TensorFlow.
- Technical Skills: Strong background in Natural Language Processing (NLP), Computer Vision (CV), or Reinforcement Learning.
- Infrastructure: Experience with cloud platforms (AWS, GCP), containerization (Docker), and orchestration (Kubernetes).
- Problem Solving: Proven track record of solving complex technical challenges in large-scale distributed systems.
- Communication: Excellent verbal and written communication skills, capable of explaining complex technical concepts to non-technical stakeholders.