Senior Associate – Quantum Computing (CTIO)
About the Commercial Technology & Innovation Office (CTIO)
The Commercial Technology & Innovation Office (CTIO) is dedicated to standardizing, automating, and delivering tools, processes, and emerging technologies—including quantum computing—that drive efficiency and enable our people to reimagine the possible. With a strong focus on process improvement, transformation, data & analytics, and alternative delivery solutions such as quantum optimization, CTIO is at the forefront of creating value for the firm. A career in CTIO provides the unique opportunity to build transformative products and innovative solutions that identify business gaps, solve complex problems, and unlock new opportunities.
Basic Qualifications
• Level: Associate / Senior Associate
• Minimum Experience: 4–8 years (including at least one year in quantum algorithms, cryptography, or quantum computing; the remainder in Generative AI/Data Science).
• Education: Graduate, Postgraduate, or PhD from reputed institutes with relevant experience.
• Field of Study: MS/MTech/PhD in Computer Science, Engineering, Physics, Mathematics, or a related technical field—or equivalent practical experience.
Knowledge & Skills
• Minimum one year of experience in quantum algorithms, cryptography, quantum computing, optimization, or machine learning.
• Strong foundation in machine learning and deep learning algorithms (e.g., random forests, ensemble methods, CNNs, DNNs).
• Proficiency with open-source frameworks such as PyTorch, TensorFlow, and Keras.
• Experience publishing in reputed international journals on quantum algorithms or quantum computing applications.
• Ability to learn new technologies rapidly and evaluate their technical and commercial impact.
Primary Skills:
• Deep understanding of linear algebra and advanced quantum computing concepts.
• Hands-on expertise with quantum algorithms, gate-based quantum systems, IBM Qiskit, and D-Wave’s annealing/optimization tools.
• Experience with quantum cryptography, quantum NLP, QUBO formulation for optimization problems.
• Strong proficiency in Python.
Secondary Skills (Preferred):
• Experience applying machine learning and deep learning techniques with TensorFlow, Keras, and Scikit-learn in Python.
• Prior research publications in leading journals.
Roles & Responsibilities
• Explore emerging analytical technologies and evaluate their technical and commercial viability.
• Develop proof-of-concepts and prototypes in sprint cycles for internal and client-facing use.
• Mentor and support junior team members.
• Rapidly test, refine, and validate hypotheses related to data processing and ML model development.
• Build AI pipelines for data ingestion, cleaning, and prediction.
• Contribute to research publications and innovative perspectives on AI/Quantum that may be shared with clients and in academic forums.
• Stay updated on cutting-edge AI and quantum research.
