Quantum Engineer

About Artificial Brain

Artificial Brain is a pioneering technology company at the forefront of quantum computing and artificial intelligence. We are dedicated to pushing the boundaries of innovation by developing cutting-edge quantum solutions integrated with advanced machine learning techniques. Join our dynamic team in Pune to shape the future of quantum technology.

Role Overview

We are seeking a highly skilled and motivated Quantum Engineer to join our R&D team in Pune. The ideal candidate will have extensive expertise in both gate-based and annealing quantum computing approaches, combined with a strong background in machine learning. This role will focus on conducting advanced research and development to design, implement, and optimize quantum algorithms and systems for real-world applications.

Key Responsibilities

• Quantum Algorithm Development: Design and develop quantum algorithms using gate-based and annealing quantum computing frameworks to solve complex computational problems.
• Machine Learning Integration: Integrate quantum computing solutions with machine learning models to enhance the performance and scalability of AI-driven applications.
• Research & Development: Conduct cutting-edge research to explore novel quantum computing techniques, hybrid quantum-classical algorithms, and their applications.
• System Optimization: Optimize quantum circuits and annealing schedules for performance, scalability, and error mitigation on various quantum hardware platforms.
• Collaboration: Work closely with cross-functional teams, including data scientists, software engineers, and physicists, to develop and deploy quantum-enhanced solutions.
• Prototyping & Testing: Build and test prototypes of quantum algorithms and systems, ensuring robustness and accuracy in real-world scenarios.
• Documentation & Reporting: Document research findings, prepare technical reports, and present results to internal teams and external stakeholders.
• Stay Updated: Keep abreast of the latest advancements in quantum computing, machine learning, and related fields to drive innovation.

Required Qualifications

Education:

• Masters or Ph.D. in Quantum Computing, Physics, Computer Science, Electrical Engineering, or a related field.

Experience:

• 2+ years of hands-on experience in quantum computing, with expertise in both gate-based quantum computing (e.g., Qiskit, Cirq, or similar) and quantum annealing (e.g., D-Wave).
• Proven experience in applying machine learning techniques (e.g., supervised/unsupervised learning, deep learning, reinforcement learning) to real-world problems.
• Strong track record in research and development, preferably in quantum computing or a related field.

Technical Skills:

• Proficiency in the Python programming language.
• Familiarity with quantum computing frameworks (e.g., Qiskit, Cirq) and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Knowledge of quantum hardware platforms and their limitations (e.g., IBM Quantum, Google Quantum, D-Wave).
• Experience with quantum machine learning (QML) algorithms
• Experience with hybrid quantum-classical algorithms and optimization techniques.

Research Skills:

• Ability to conduct independent research, analyze complex datasets, and publish findings in peer-reviewed journals or conferences.

Soft Skills:

• Strong problem-solving skills, excellent communication, and ability to work collaboratively in a fast-paced, interdisciplinary environment.

Why Join Artificial Brain:

• Innovative Environment: Work on groundbreaking projects at the intersection of quantum computing and artificial intelligence.
• Impactful Work: Contribute to transformative technologies that have the potential to revolutionize industries.
• Growth Opportunities: Access to continuous learning, professional development, and collaboration with world-class experts.
• Inclusive Culture: Be part of a diverse and inclusive team that values creativity, curiosity, and innovation.

Location:

• This position is based inPune, India, with opportunities for on-site work in the UAE and the U.S., depending on project requirements.