Research Engineer

Location: IN KA Bengaluru, IN MH Mumbai Eureka

Time Type: Full time

Job Description

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.


If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

Key Responsibilities

• Design and implement quantum-assisted hybrid algorithms for optimization, simulation, machine learning, and generative modeling across real-world industry use cases.

• Develop, debug, and optimize quantum workloads while applying techniques across different hardware and frameworks.

• Improve existing algorithm efficiency through transpilation, circuit depth reduction, Hamiltonian formulation, shot optimization, and error correction strategies.

• Collaborate with interdisciplinary teams to translate quantum research into practical, scalable solutions aligned with industry needs.

• Contribute to intellectual property and thought leadership through patents, publications, and technical content.

• Mentor junior researchers and engineers while fostering collaborative brainstorming and sharing perspectives on technical best practices.

Required Skills

• Bachelor/Master’s degree with 3+ years of industry experience or PhD in Quantum Computing, Physics, Chemistry, Computer Science, Electrical Engineering, or a related field.

• Strong hands-on experience with quantum programming frameworks (e.g., Qiskit, Cirq, PennyLane) and hybrid quantum–classical systems.

• Demonstrated experience working with real quantum hardware and platforms (e.g., IBM Quantum, AWS Braket, Google Quantum, or related hardware) and familiarity with the nuances behind superconducting qubits, trapped ions, and neutral atoms.

• Solid understanding of quantum algorithms, quantum machine learning, and classical machine learning techniques (deep learning, optimization, reinforcement learning, generative models).

• Experience with transpilation, circuit optimization, error correction, and performance evaluation on noisy quantum devices.

• Domain knowledge in at least one industry (e.g., finance, healthcare, materials, manufacturing, or logistics).

• Proven ability to translate research concepts into practical, industry-relevant solutions, with a demonstrated track record of patents, peer-reviewed publications, or equivalent applied research outputs.

• Experience with managing/mentoring junior engineers, including conducting code and design architecture reviews following best practices.