Job Description
We are pioneering the 2026 standard of computing by bridging the gap between quantum mechanics and artificial intelligence. At Nebula Dynamics, we are not just building software; we are architecting the infrastructure for a future where computation is instantaneous and limitless.
As our AI & Quantum Computing Lead, you will spearhead the development of hybrid quantum-classical algorithms that solve problems currently deemed unsolvable. If you are a visionary engineer looking to define the trajectory of future tech, we want to hear from you.
Why Join Us?
- Work on high-impact projects that define the next decade of technology.
- Competitive compensation package and equity options.
- State-of-the-art R&D lab in the heart of the tech hub.
Are you ready to shape the future? Apply now.
Responsibilities
- Architect Solutions: Design and implement scalable quantum-AI hybrid systems that integrate seamlessly with existing cloud infrastructure.
- R&D Leadership: Lead a team of top-tier researchers in exploring novel quantum algorithms for machine learning applications.
- System Integration: Bridge the gap between quantum processors and classical AI frameworks to optimize performance and latency.
- Strategic Vision: Define the technical roadmap for our quantum computing initiatives, ensuring alignment with business goals and industry standards.
- Prototyping: Rapidly prototype and validate cutting-edge technologies to de-risk development cycles.
- Mentorship: Foster a culture of innovation by mentoring junior engineers and researchers.
Qualifications
- Education: Master’s or PhD in Computer Science, Physics, Mathematics, or a related field with a focus on Quantum Computing or Artificial Intelligence.
- Experience: Minimum 5 years of experience in software engineering, with 2+ years specifically in quantum computing or advanced AI/ML architectures.
- Technical Skills: Proficiency in Python, C++, or Rust; experience with quantum programming frameworks (e.g., Qiskit, Cirq, PennyLane).
- Domain Knowledge: Deep understanding of linear algebra, probability theory, and optimization algorithms.
- Problem Solving: Demonstrated ability to tackle complex, ill-defined problems with creative engineering solutions.
- Communication: Excellent ability to translate complex technical concepts into clear business value for stakeholders.