Job Description
We are pioneering the technological landscape of 2026, building the infrastructure for the next generation of artificial intelligence and autonomous systems. As a Senior AI & Future Tech Architect at Aethel Systems, you will not just manage code; you will define the architecture of tomorrow. We are looking for a visionary engineer to bridge the gap between cutting-edge research in generative models and scalable, production-grade systems.
In this role, you will lead high-impact projects that push the boundaries of what is possible in machine learning, ensuring our solutions are ethical, efficient, and transformative.
Responsibilities
- Architect Scalable AI Solutions: Design and implement robust neural network architectures and machine learning pipelines capable of handling petabyte-scale data.
- Pioneer Future Tech Integration: Lead the research and integration of emerging technologies, including advanced reinforcement learning and quantum-assisted algorithms.
- System Optimization: Oversee the deployment, monitoring, and optimization of models to ensure high availability, low latency, and maximum throughput.
- Team Leadership & Mentorship: Guide a team of talented data scientists and engineers, fostering a culture of innovation, continuous learning, and technical excellence.
- Ethical AI Governance: Establish and enforce best practices for data privacy, algorithmic bias, and responsible AI deployment.
- Strategic Roadmapping: Collaborate with cross-functional stakeholders to align technical roadmaps with long-term business objectives and future tech trends.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, Robotics, or a related technical field.
- Experience: 8+ years of professional experience in software engineering or machine learning, with at least 3 years in a senior or architect-level role.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, or JAX. Strong background in distributed computing systems and cloud infrastructure (AWS, GCP, or Azure).
- Research Background: Proven track record of publishing in top-tier AI conferences (NeurIPS, ICML, ICLR) or contributing to open-source machine learning frameworks.
- Problem Solving: Demonstrated ability to tackle complex, unstructured problems and deliver innovative engineering solutions.
- Communication: Excellent verbal and written communication skills, with the ability to translate complex technical concepts for diverse audiences.