Job Description
Are you ready to shape the future of technology?
Aether Systems Inc. is pioneering the 2026 Vision initiative, a groundbreaking project aimed at redefining the boundaries of Generative AI and Quantum-Enhanced Machine Learning. We are seeking a visionary Senior AI Architect to lead our research and development efforts in building the intelligent systems of tomorrow.
In this role, you will not just write code; you will architect the cognitive frameworks that will drive industry transformation. If you are passionate about pushing the envelope of what is possible in AI and have a deep understanding of scalable systems, we want to meet you.
Why Join Us?
- Work at the forefront of the 2026 technological revolution.
- Competitive equity package and comprehensive benefits.
- Flexible remote-first policy with hubs in San Francisco and New York.
Key Responsibilities:
Responsibilities
- Design and implement the core architectural framework for the 2026 AI ecosystem, ensuring scalability and ethical integrity.
- Lead the research and development of next-generation Large Language Models (LLMs) and predictive analytics engines.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate strategic vision into technical reality.
- Optimize neural network architectures for high-performance computing environments and edge devices.
- Establish best practices for AI governance, transparency, and security within the organization.
- Conduct rigorous testing and validation of AI models to ensure accuracy and reliability in real-world scenarios.
- Mentor junior engineers and researchers, fostering a culture of continuous innovation.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field (or equivalent practical experience).
- Minimum of 7+ years of experience in software engineering, with a specific focus on AI/ML.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of deploying large-scale machine learning models into production environments.
- Strong understanding of MLOps, cloud infrastructure (AWS/GCP/Azure), and containerization (Docker/Kubernetes).
- Excellent problem-solving skills and the ability to thrive in a fast-paced, ambiguous environment.
- Experience with ethical AI frameworks and bias mitigation techniques.