Research Engineer

Quantum Machine Learning – Research Engineer

Experience:

Location: Bangalore/Mumbai

Background and Objective

Quantiphi is a global AI-first digital engineering company that bridges cutting-edge research with real-world business impact across Generative AI, Digital Twins, Life Sciences, and Quantum Computing. Its R&D arm, Phi Labs, drives applied innovation through advanced research, patents, publications, and technology transfer across high-impact areas.

As part of our Quantum Computing team expansion, we are looking for a hands-on Research Engineer who operates at the intersection of industrial research, software engineering, and business problem-solving.

This role is ideal for someone who understands how to translate stakeholder and business requirements into technically feasible solutions, evaluate where classical, quantum-inspired, or hybrid quantum-classical approaches can create value, and build practical solutions that evolve into reusable assets, intellectual property, publications, workshops, and client-facing thought leadership.

You will work closely with other researchers, engineers, and business teams to identify meaningful use cases across industries such as finance, healthcare, life sciences, materials, manufacturing, and logistics. The focus for this role is not just on quantum algorithm development; it requires understanding business context, framing the right technical problem, engineering robust solutions, and communicating outcomes clearly to both technical and non-technical stakeholders.

Key Responsibilities

• Design, develop, and evaluate hands-on engineering solutions that explore the use of quantum, quantum-inspired, and hybrid quantum-classical methods for real-world business problems.
• Work with internal teams, researchers, and client-facing stakeholders to understand business requirements and assess what it takes to translate them into quantum-relevant problem formulations.
• Build practical proof-of-concepts, reusable code artifacts, benchmarks, and technical assets that demonstrate the applicability of quantum approaches in industrial settings.
• Collaborate with interdisciplinary research teams to contribute to patents, publications, technical blogs, whitepapers, workshops, and other thought-leadership initiatives.
• Apply strong software engineering practices to develop scalable and maintainable code across quantum and classical machine learning workflows.
• Engage in knowledge dissemination through internal workshops, external presentations, technical content, and mentoring of junior researchers or engineers.
• Contribute to architectural decisions, code reviews, technical design discussions, and engineering best practices across research initiatives.
• Stay current with developments in quantum computing, quantum machine learning, quantum-inspired algorithms, and industrial applications, while critically evaluating their practical readiness.

Required Skills

• Bachelor's or Master's degree with 3+ years of relevant industry experience, or a PhD in Quantum Computing, Physics, Chemistry, Computer Science, Electrical Engineering, Applied Mathematics, or a related field.
• Strong hands-on engineering experience in Python and modern software development practices, including clean code, testing, version control, documentation, and collaborative development.
• Experience working in industrial research, applied R&D, technology consulting, product engineering, or client-facing innovation environments.
• Hands-on experience with machine learning, optimization, generative models, simulation, or data-driven decision systems in practical business contexts.
• Working knowledge of quantum computing concepts, quantum machine learning, hybrid quantum-classical approaches, or quantum-inspired methods.
• Experience with one or more quantum programming frameworks such as Qiskit, PennyLane, Cirq, Amazon Braket, or similar platforms.
• Domain knowledge in at least one industry area, preferably finance, healthcare, life sciences, manufacturing, logistics, or materials science.
• Demonstrated ability to convert research concepts into applied outcomes such as prototypes, reusable assets, technical reports, patents, publications, blogs, workshops, or client-facing demonstrations.
• Strong communication skills with the ability to work across research, engineering, business, and domain expert teams.
• Experience mentoring junior engineers or researchers, reviewing code, contributing to technical design, and promoting engineering best practices.

Good to Have

• Prior hands-on experience working with quantum hardware or cloud-based quantum platforms such as IBM Quantum, AWS Braket, Google Quantum, DWave Annealers, or similar systems.
• Familiarity with practical considerations in noisy quantum systems, including device constraints, execution workflows, measurement strategies, and performance evaluation.
• Experience applying advanced analytics, AI, ML, or simulation techniques to business problems in finance or healthcare.
• Prior experience in consulting, applied research labs, innovation teams, or technology transfer environments.
• Track record of patents, peer-reviewed publications, technical blogs, conference talks, workshops, or other thought-leadership contributions.
• Experience translating emerging technologies into stakeholder-facing narratives, demos, proposals, or solution blueprints.

Preferred Profile

The ideal candidate is a strong hands-on engineer with an applied research mindset. They should be comfortable moving from ambiguous business requirements to structured technical problem statements, building prototypes, evaluating feasibility, and communicating outcomes clearly. Prior quantum experience is valuable, but candidates with a strong record of delivering business-relevant AI, ML, simulation, or advanced analytics solutions—especially in finance or healthcare—will also be considered.