Job Description
Join us as a Chief Machine Learning Architect and help us push Quantum Machine Learning forward within Quantum Computing & Technology.
You'll be working out of Jaipur (hybrid), and honestly, the day-to-day is going to revolve around Statistical Analysis and Quantum Circuit Design. We're not looking for someone who just ticks boxes - we want someone who actually cares about quantum machine learning.
On paper, we'd expect M.Sc/M.Tech (Quantum Computing) and somewhere around 10 years of experience, but we're just as interested in how you think as in what's on your resume.
Pay-wise, we're offering INR 48.6-87.9 LPA - fair for the senior level band and open to discussion based on what you bring.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. 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.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. The next logical step from this position is a senior or lead-track role within the same function.
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.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. High performers in this role typically move into a broader ownership scope within 18-24 months.
The organisation has historically promoted from within for a majority of its senior and lead openings. Interested candidates should be prepared to walk through relevant past work during the interview process.
Learning and certification support is available for tools and frameworks directly relevant to the role. Compensation includes standard statutory benefits along with performance-linked variable pay. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
You'll be working out of Jaipur (hybrid), and honestly, the day-to-day is going to revolve around Statistical Analysis and Quantum Circuit Design. We're not looking for someone who just ticks boxes - we want someone who actually cares about quantum machine learning.
On paper, we'd expect M.Sc/M.Tech (Quantum Computing) and somewhere around 10 years of experience, but we're just as interested in how you think as in what's on your resume.
Pay-wise, we're offering INR 48.6-87.9 LPA - fair for the senior level band and open to discussion based on what you bring.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. 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.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. The next logical step from this position is a senior or lead-track role within the same function.
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.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. High performers in this role typically move into a broader ownership scope within 18-24 months.
The organisation has historically promoted from within for a majority of its senior and lead openings. Interested candidates should be prepared to walk through relevant past work during the interview process.
Learning and certification support is available for tools and frameworks directly relevant to the role. Compensation includes standard statutory benefits along with performance-linked variable pay. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.