Position: Research Engineer - Quantum HPC
Company: Quantum Computing Startup
Category: Python
Experience required: 3y
English level: upper

We are a stealth-mode Quantum Computing startup that builds enabling quantum software to run scalable applications on a modern noisy quantum hardware. Startup has a founding team of Stanford and the Weizmann Institute of Science alumni, graduated from a world leading deep-tech accelerator and is backed by some of Silicon Valley’s leading investors. 


**About the role:**

As a Quantum HPC expert, you will explore bleeding edge approaches in performance optimisation and HPC workflows for Quantum Algorithms. Your aim is to maximise the utility of NISQ-era quantum processing units (QPU) and the addressable scale of quantum applications.

You will run and guide R&D projects on performance acceleration and monitoring,  efficient characterisation, benchmarking, use-case applicability, and limitations of distributed computing schemes for quantum algorithms.

**Required skills & expertise:**

- MSc in Computer Science, Physics or related Applied Science field (Electrical Engineering, Quantum Chemistry, etc.)
- 3+ years of experience with distributed or high-performance computing systems
- Experience with parallel programming using MPI, OpenMP or similar frameworks and handling asynchronous tasks and scheduling.
- Experience with developing algorithms performance monitoring tools
- Solid programming skills (Python, С/C++)
- Core scientific Python stack (numpy, scipy) 
- Excellent algorithms development and analysis skills 
- Experience with modern Cloud platforms (AWS, GCP, Azure)
- Strong communication skills (high-profile conference presentations, scientific writing)
- Proactiveness and creativity in learning new ideas

**Bonus:**

- PhD in Computer Science, Physics or related Applied Science field (Electrical Engineering, Quantum Chemistry, etc.)
- Experience with GPU programming and CUDA
- Background in any of: scientific distributed computing, computational physics, high-performance scientific programming, quantum condensed matter physics simulations.
- Understanding of core quantum algorithms (Grover, QFT, Deutsch-Josza, VQE, QAOA)
- Experience with quantum development software (Qiskit, Pennylane, Braket)
- Experience with applied machine learning frameworks (PyTorch, TensorFlow)