Job Description
This position calls for a Lead Quantum Machine Learning Analyst who can take ownership of core responsibilities within our Quantum Machine Learning team. This is a mid level opening based out of Remote (Pan India), offered on a contract basis.
The ideal candidate holds B.Tech (CS/Physics) and brings roughly 5 years of hands-on exposure to quantum machine learning. Day-to-day, the work draws heavily on Cloud Quantum Platforms (IBM Q/Azure Quantum), Quantum Machine Learning, Research Documentation, Quantum Algorithms, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 28.6-51.3 LPA, in line with market standards for mid level roles within quantum computing & technology.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Learning and certification support is available for tools and frameworks directly relevant to the role. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Compensation includes standard statutory benefits along with performance-linked variable pay.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. The organisation has historically promoted from within for a majority of its senior and lead openings.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
Internal job postings are open to employees who've completed a minimum tenure in their current role. Mornings are usually spent on planning and status reviews, while the rest of the day is given over to hands-on delivery and problem-solving. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
References may be requested closer to the offer stage rather than at the start of the process. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
Interested candidates should be prepared to walk through relevant past work during the interview process. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
If your background aligns with the above and you're looking for your next step in Quantum Machine Learning, we'd like to hear from you.
The ideal candidate holds B.Tech (CS/Physics) and brings roughly 5 years of hands-on exposure to quantum machine learning. Day-to-day, the work draws heavily on Cloud Quantum Platforms (IBM Q/Azure Quantum), Quantum Machine Learning, Research Documentation, Quantum Algorithms, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 28.6-51.3 LPA, in line with market standards for mid level roles within quantum computing & technology.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Learning and certification support is available for tools and frameworks directly relevant to the role. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Compensation includes standard statutory benefits along with performance-linked variable pay.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. The organisation has historically promoted from within for a majority of its senior and lead openings.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
Internal job postings are open to employees who've completed a minimum tenure in their current role. Mornings are usually spent on planning and status reviews, while the rest of the day is given over to hands-on delivery and problem-solving. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
References may be requested closer to the offer stage rather than at the start of the process. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
Interested candidates should be prepared to walk through relevant past work during the interview process. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
If your background aligns with the above and you're looking for your next step in Quantum Machine Learning, we'd like to hear from you.