Job Description
Position: AI Platform Product Director
Function: AI Product Management
Industry: Machine Learning
Grade: senior level
Location: Mumbai
Employment Type: Leadership - Full-time
Compensation: INR 11.3-41.1 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with ai product management, in accordance with the standards and processes laid down by Machine Learning.
Minimum Qualification: M.Sc (Data Science)
Minimum Experience: 15 years
Core Competencies Required: Data Preprocessing, TensorFlow/PyTorch, Model Evaluation & Tuning, Machine Learning Algorithms, Statistical Modelling, Cloud Platforms (AWS/GCP), Deep Learning, Python, AI Product Management
Further Information:
Compensation includes standard statutory benefits along with performance-linked variable pay. Learning and certification support is available for tools and frameworks directly relevant to the role. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. 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. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Internal job postings are open to employees who've completed a minimum tenure in their current role. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The organisation has historically promoted from within for a majority of its senior and lead openings. 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. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Interested candidates should be prepared to walk through relevant past work during the interview process. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. The package is structured with a fixed component, performance bonus, and standard health coverage. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Most days include at least one review checkpoint where progress is discussed against the plan for the week. 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.
Function: AI Product Management
Industry: Machine Learning
Grade: senior level
Location: Mumbai
Employment Type: Leadership - Full-time
Compensation: INR 11.3-41.1 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with ai product management, in accordance with the standards and processes laid down by Machine Learning.
Minimum Qualification: M.Sc (Data Science)
Minimum Experience: 15 years
Core Competencies Required: Data Preprocessing, TensorFlow/PyTorch, Model Evaluation & Tuning, Machine Learning Algorithms, Statistical Modelling, Cloud Platforms (AWS/GCP), Deep Learning, Python, AI Product Management
Further Information:
Compensation includes standard statutory benefits along with performance-linked variable pay. Learning and certification support is available for tools and frameworks directly relevant to the role. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. 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. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Internal job postings are open to employees who've completed a minimum tenure in their current role. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The organisation has historically promoted from within for a majority of its senior and lead openings. 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. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Interested candidates should be prepared to walk through relevant past work during the interview process. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. The package is structured with a fixed component, performance bonus, and standard health coverage. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Most days include at least one review checkpoint where progress is discussed against the plan for the week. 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.