Job Description
We are at the forefront of innovation, pioneering the technological advancements that will define the year 2026. We are seeking a visionary Quantum AI Researcher to join our elite engineering team in San Francisco. In this role, you will bridge the gap between classical artificial intelligence and the emerging power of quantum computing, building the systems that will revolutionize data processing and predictive modeling.
As a key player in our R&D division, you will have the autonomy to explore uncharted territories in algorithmic development, working on projects that will shape the future of the digital landscape. If you are passionate about the convergence of quantum mechanics and machine learning, and you want to build the technology of tomorrow, today, we want to hear from you.
Responsibilities
- Design and implement advanced quantum algorithms for machine learning tasks, specifically optimized for the 2026 computational era.
- Collaborate with theoretical physicists and software engineers to integrate quantum hardware into scalable AI frameworks.
- Analyze and mitigate noise in quantum processors to improve model accuracy and reliability.
- Conduct research on quantum supremacy and its applications in predictive analytics and autonomous systems.
- Document complex research findings and contribute to open-source quantum computing libraries.
- Lead technical discussions on the future trajectory of AI and quantum integration within the industry.
Qualifications
- PhD or Master’s degree in Computer Science, Physics, Mathematics, or a related field with a focus on quantum mechanics.
- Extensive experience with quantum programming frameworks (Qiskit, Cirq, or Pennylane).
- Strong proficiency in Python and C++ for backend development and simulation.
- Deep understanding of classical machine learning techniques (TensorFlow, PyTorch) and how they translate to quantum environments.
- Experience with cloud-based quantum computing platforms (IBM Quantum, AWS Braket, or Google Cirq).
- Familiarity with optimization problems, linear algebra, and statistical mechanics.