Job Description
Quantum Computing & Technology is looking for an experienced Quantum Machine Learning Strategy Analyst to take ownership of the Quantum Machine Learning charter at a mid level. This is a role for someone who has already operated at scale and is comfortable setting direction rather than simply following one.
The successful candidate will bring approximately 5 years of progressively senior experience, holding M.Sc/M.Tech (Quantum Computing), with a demonstrated track record across Machine Learning Basics, Python Programming, Qiskit/Cirq Programming, Quantum Machine Learning, Research Documentation. Beyond individual capability, this role expects the person to mentor junior team members and represent the function in cross-departmental discussions.
Reporting relationships will be defined based on the final scope agreed at offer stage, and the role is based out of Chandigarh on a full-time arrangement. Compensation is benchmarked at INR 5.3-35.7 LPA, reflecting the seniority and scope of the position.
Success in this role will be measured less by task completion and more by the quality of judgement applied to ambiguous, high-stakes situations within quantum machine learning.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
The package is structured with a fixed component, performance bonus, and standard health coverage. The next logical step from this position is a senior or lead-track role within the same function.
High performers in this role typically move into a broader ownership scope within 18-24 months. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Compensation includes standard statutory benefits along with performance-linked variable pay.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
References may be requested closer to the offer stage rather than at the start of the process. Learning and certification support is available for tools and frameworks directly relevant to the role. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
The successful candidate will bring approximately 5 years of progressively senior experience, holding M.Sc/M.Tech (Quantum Computing), with a demonstrated track record across Machine Learning Basics, Python Programming, Qiskit/Cirq Programming, Quantum Machine Learning, Research Documentation. Beyond individual capability, this role expects the person to mentor junior team members and represent the function in cross-departmental discussions.
Reporting relationships will be defined based on the final scope agreed at offer stage, and the role is based out of Chandigarh on a full-time arrangement. Compensation is benchmarked at INR 5.3-35.7 LPA, reflecting the seniority and scope of the position.
Success in this role will be measured less by task completion and more by the quality of judgement applied to ambiguous, high-stakes situations within quantum machine learning.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
The package is structured with a fixed component, performance bonus, and standard health coverage. The next logical step from this position is a senior or lead-track role within the same function.
High performers in this role typically move into a broader ownership scope within 18-24 months. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Compensation includes standard statutory benefits along with performance-linked variable pay.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
References may be requested closer to the offer stage rather than at the start of the process. Learning and certification support is available for tools and frameworks directly relevant to the role. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.