Job Description
AI Product Portfolio Manager | Indore | INR 8.4-35.1 LPA
AI Product Management role, mid level, full-time.
Need: M.Tech (AI/ML), 4+ yrs.
Core skills: Deep Learning, Natural Language Processing, TensorFlow/PyTorch, Python, Cloud Platforms (AWS/GCP/Azure).
If this fits your profile in ai product management, apply now.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
The package is structured with a fixed component, performance bonus, and standard health coverage. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. 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.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
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. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
References may be requested closer to the offer stage rather than at the start of the process. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. The organisation has historically promoted from within for a majority of its senior and lead openings.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
Internal job postings are open to employees who've completed a minimum tenure in their current role. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. The next logical step from this position is a senior or lead-track role within the same function.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
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. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
AI Product Management role, mid level, full-time.
Need: M.Tech (AI/ML), 4+ yrs.
Core skills: Deep Learning, Natural Language Processing, TensorFlow/PyTorch, Python, Cloud Platforms (AWS/GCP/Azure).
If this fits your profile in ai product management, apply now.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
The package is structured with a fixed component, performance bonus, and standard health coverage. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. 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.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
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. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
References may be requested closer to the offer stage rather than at the start of the process. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. The organisation has historically promoted from within for a majority of its senior and lead openings.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
Internal job postings are open to employees who've completed a minimum tenure in their current role. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. The next logical step from this position is a senior or lead-track role within the same function.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
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. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.