Job Description
We are on the brink of a technological revolution, and Nebula Future Systems is leading the charge. As we define the standards for 2026 and beyond, we are seeking a visionary Future-Ready AI & Quantum Systems Lead to bridge the gap between classical computing and next-gen quantum intelligence.
In this pivotal role, you will architect the computational backbone for our upcoming suite of generative AI tools. You will not just build software; you will engineer the paradigms that will define the industry for the next decade.
Why Join Us?
- Work with a team of elite engineers pushing the boundaries of what is possible.
- Shape the roadmap for 2026 technology adoption.
- Competitive compensation and equity packages.
Are you ready to build the future? Apply today.
Responsibilities
- Architecting Quantum-Classical Integration: Design and implement hybrid systems that leverage the power of quantum computing to solve complex, unsolvable classical problems.
- System Roadmap: Lead the technical strategy for integrating emerging 2026-era AI frameworks into our core infrastructure.
- Team Leadership: Mentor a high-performing team of AI engineers and data scientists, fostering a culture of innovation and excellence.
- Algorithm Optimization: Refine neural network architectures to maximize efficiency and reduce latency in distributed environments.
- Prototyping: Build rapid prototypes for new quantum algorithms and AI agents to validate concepts before full-scale deployment.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Physics, Mathematics, or a related field with a focus on Computational Intelligence.
- Experience: 7+ years of experience in software engineering, with at least 3 years specifically in AI/ML architecture and quantum computing research.
- Technical Skills: Proficiency in Python, C++, and Rust. Experience with quantum programming frameworks (Qiskit, Cirq) and classical ML libraries (PyTorch, TensorFlow).
- Leadership: Proven track record of leading technical teams and delivering complex projects on tight deadlines.
- Forward-Thinking: Deep understanding of current and future trends in AI, including Large Language Models (LLMs) and neuromorphic computing.