Job Description
## Chief Generative AI Scientist
**Department:** Generative AI | **Industry:** Machine Learning
**Location:** Hybrid - Bengaluru | **Job Type:** Full-time | **CTC:** INR 46.9-107.1 LPA
### Role Overview
This position calls for a Chief Generative AI Scientist who can take ownership of core responsibilities within our Generative AI team. The role is positioned at the senior level and reports into the broader Generative AI charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to generative ai.
- Apply working knowledge of Deep Learning and Computer Vision/NLP Basics to daily execution.
- Coordinate with cross-functional stakeholders within Machine Learning.
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Tech (Machine Learning) or equivalent qualification.
- 9 years of relevant experience (senior level).
- Working proficiency in: Deep Learning, Computer Vision/NLP Basics, Generative AI, Data Preprocessing, TensorFlow/PyTorch, MLOps, Cloud Platforms (AWS/GCP), Python.
### Additional Notes
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. The package is structured with a fixed component, performance bonus, and standard health coverage. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Compensation includes standard statutory benefits along with performance-linked variable pay. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Most days include at least one review checkpoint where progress is discussed against the plan for the week. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Learning and certification support is available for tools and frameworks directly relevant to the role. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. The organisation has historically promoted from within for a majority of its senior and lead openings. References may be requested closer to the offer stage rather than at the start of the process. High performers in this role typically move into a broader ownership scope within 18-24 months. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. There is a defined internal mobility path for people who want to specialise deeper or move into people management. 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. The next logical step from this position is a senior or lead-track role within the same function. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
**Department:** Generative AI | **Industry:** Machine Learning
**Location:** Hybrid - Bengaluru | **Job Type:** Full-time | **CTC:** INR 46.9-107.1 LPA
### Role Overview
This position calls for a Chief Generative AI Scientist who can take ownership of core responsibilities within our Generative AI team. The role is positioned at the senior level and reports into the broader Generative AI charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to generative ai.
- Apply working knowledge of Deep Learning and Computer Vision/NLP Basics to daily execution.
- Coordinate with cross-functional stakeholders within Machine Learning.
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Tech (Machine Learning) or equivalent qualification.
- 9 years of relevant experience (senior level).
- Working proficiency in: Deep Learning, Computer Vision/NLP Basics, Generative AI, Data Preprocessing, TensorFlow/PyTorch, MLOps, Cloud Platforms (AWS/GCP), Python.
### Additional Notes
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. The package is structured with a fixed component, performance bonus, and standard health coverage. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Compensation includes standard statutory benefits along with performance-linked variable pay. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Most days include at least one review checkpoint where progress is discussed against the plan for the week. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Learning and certification support is available for tools and frameworks directly relevant to the role. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. The organisation has historically promoted from within for a majority of its senior and lead openings. References may be requested closer to the offer stage rather than at the start of the process. High performers in this role typically move into a broader ownership scope within 18-24 months. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. There is a defined internal mobility path for people who want to specialise deeper or move into people management. 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. The next logical step from this position is a senior or lead-track role within the same function. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.