Job Description
We are seeking a visionary Quantum AI Research Engineer to spearhead our R&D division. As we prepare to redefine the technological landscape of 2026, you will be at the forefront of merging quantum computing with advanced artificial intelligence. This is not just a job; it is an opportunity to build the core intelligence of the future.
Why Join Us?
At Aetheria Futures, we operate at the intersection of physics and software. Our mission is to deliver quantum-advantage solutions for enterprise-level challenges. You will work in a high-performance environment with state-of-the-art hardware and a team of elite scientists and engineers.
The Role
You will be responsible for designing, implementing, and testing quantum algorithms that solve complex machine learning problems. Your work will bridge the gap between theoretical quantum mechanics and practical, deployable AI models.
Responsibilities
- Algorithm Development: Design and implement novel quantum algorithms to accelerate machine learning tasks and optimize neural network training.
- Hybrid Modeling: Develop hybrid quantum-classical models that leverage the strengths of both classical and quantum hardware to solve real-world problems.
- R&D Leadership: Lead internal research initiatives and publish findings in top-tier scientific conferences (e.g., NeurIPS, QIP).
- Prototype Engineering: Build scalable prototypes and proof-of-concepts for enterprise clients using cloud-based quantum processors.
- Collaboration: Partner with cross-functional teams including data scientists, quantum physicists, and software engineers to integrate quantum capabilities into existing AI stacks.
- Technical Mentorship: Mentor junior researchers and guide them in the rapidly evolving field of quantum machine learning.
Qualifications
- Education: Ph.D. in Computer Science, Physics, Mathematics, or a related field (or equivalent industry experience).
- Technical Skills: Proficiency in Python, C++, and ML frameworks (TensorFlow, PyTorch).
- Quantum Experience: Hands-on experience with quantum computing libraries (Qiskit, Cirq, or PennyLane).
- Mathematics: Strong background in linear algebra, probability, and calculus.
- Problem Solving: Demonstrated ability to tackle complex, abstract problems and translate them into technical solutions.
- Communication: Excellent verbal and written communication skills for technical presentations and documentation.