Job Description
Machine Learning is looking for an experienced Generative AI Architect to take ownership of the Generative AI charter at a senior 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 13 years of progressively senior experience, holding M.Tech (Machine Learning), with a demonstrated track record across Generative AI, MLOps, Deep Learning, Python, Computer Vision/NLP Basics. 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 Hybrid - Pune on a leadership - full-time arrangement. Compensation is benchmarked at INR 42.0-71.3 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 generative ai.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
Internal job postings are open to employees who've completed a minimum tenure in their current role. Relocation assistance may be extended for candidates moving from a different city, subject to approval. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
The organisation has historically promoted from within for a majority of its senior and lead openings. Most days include at least one review checkpoint where progress is discussed against the plan for the week. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
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.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. 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. The next logical step from this position is a senior or lead-track role within the same function.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
The package is structured with a fixed component, performance bonus, and standard health coverage. Compensation includes standard statutory benefits along with performance-linked variable pay.
The successful candidate will bring approximately 13 years of progressively senior experience, holding M.Tech (Machine Learning), with a demonstrated track record across Generative AI, MLOps, Deep Learning, Python, Computer Vision/NLP Basics. 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 Hybrid - Pune on a leadership - full-time arrangement. Compensation is benchmarked at INR 42.0-71.3 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 generative ai.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
Internal job postings are open to employees who've completed a minimum tenure in their current role. Relocation assistance may be extended for candidates moving from a different city, subject to approval. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
The organisation has historically promoted from within for a majority of its senior and lead openings. Most days include at least one review checkpoint where progress is discussed against the plan for the week. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
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.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. 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. The next logical step from this position is a senior or lead-track role within the same function.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
The package is structured with a fixed component, performance bonus, and standard health coverage. Compensation includes standard statutory benefits along with performance-linked variable pay.