Job Description
Join FutureForge Labs at the forefront of technological evolution as we pioneer the next generation of quantum-AI hybrid systems. Our multidisciplinary team is redefining computational boundaries to solve humanity's most complex challenges. This role offers unparalleled opportunity to shape the 2026 technological landscape while working in our state-of-the-art San Francisco facility with world-class resources and collaborative environment.
We offer competitive compensation, equity packages, comprehensive benefits, and dedicated innovation time to explore cutting-edge projects. Our culture values intellectual curiosity, rapid iteration, and breakthrough thinking.
Responsibilities
- Design and implement quantum algorithms leveraging machine learning for optimization problems
- Develop hybrid quantum-classical computing frameworks for real-world applications
- Lead research initiatives in quantum error correction and fault-tolerant systems
- Collaborate with hardware teams to bridge theoretical models with physical implementations
- Publish peer-reviewed research and present findings at leading conferences
- Mentor junior researchers and contribute to open-source quantum development
- Identify commercial applications for emerging quantum technologies
Qualifications
- PhD in Quantum Computing, Physics, Computer Science, or related field
- 3+ years experience with quantum programming frameworks (Qiskit, Cirq, or PennyLane)
- Expertise in machine learning frameworks (PyTorch, TensorFlow) with quantum integration
- Strong background in linear algebra, quantum mechanics, and information theory
- Published research in quantum computing or quantum machine learning
- Experience with cloud quantum computing platforms (IBM Quantum, Amazon Braket)
- Demonstrated ability to translate complex theoretical concepts into practical implementations