Job Description
## Chief AI Scientist
**Department:** AI Research & Development | **Industry:** Artificial Intelligence (AI)
**Location:** Nagpur | **Job Type:** Full-time | **CTC:** INR 51.8-94.7 LPA
### Role Overview
An opening exists for a Chief AI Scientist to join the Artificial Intelligence (AI) vertical, focused on AI Research & Development. The role is positioned at the senior level and reports into the broader AI Research & Development charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to ai research & development.
- Apply working knowledge of Deep Learning and Development to daily execution.
- Coordinate with cross-functional stakeholders within Artificial Intelligence (AI).
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Tech (AI/ML) or equivalent qualification.
- 13 years of relevant experience (senior level).
- Working proficiency in: Deep Learning, Development, TensorFlow/PyTorch, Neural Network Architectures, Natural Language Processing, AI Research.
### Additional Notes
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. Interested candidates should be prepared to walk through relevant past work during the interview process. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Learning and certification support is available for tools and frameworks directly relevant to the role. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Internal job postings are open to employees who've completed a minimum tenure in their current role. The next logical step from this position is a senior or lead-track role within the same function. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. 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. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. 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. Relocation assistance may be extended for candidates moving from a different city, subject to approval. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Most days include at least one review checkpoint where progress is discussed against the plan for the week. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. 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. 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. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. The organisation has historically promoted from within for a majority of its senior and lead openings. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Compensation includes standard statutory benefits along with performance-linked variable pay. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. High performers in this role typically move into a broader ownership scope within 18-24 months. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. The package is structured with a fixed component, performance bonus, and standard health coverage. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
**Department:** AI Research & Development | **Industry:** Artificial Intelligence (AI)
**Location:** Nagpur | **Job Type:** Full-time | **CTC:** INR 51.8-94.7 LPA
### Role Overview
An opening exists for a Chief AI Scientist to join the Artificial Intelligence (AI) vertical, focused on AI Research & Development. The role is positioned at the senior level and reports into the broader AI Research & Development charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to ai research & development.
- Apply working knowledge of Deep Learning and Development to daily execution.
- Coordinate with cross-functional stakeholders within Artificial Intelligence (AI).
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Tech (AI/ML) or equivalent qualification.
- 13 years of relevant experience (senior level).
- Working proficiency in: Deep Learning, Development, TensorFlow/PyTorch, Neural Network Architectures, Natural Language Processing, AI Research.
### Additional Notes
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. Interested candidates should be prepared to walk through relevant past work during the interview process. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Learning and certification support is available for tools and frameworks directly relevant to the role. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Internal job postings are open to employees who've completed a minimum tenure in their current role. The next logical step from this position is a senior or lead-track role within the same function. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. 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. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. 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. Relocation assistance may be extended for candidates moving from a different city, subject to approval. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Most days include at least one review checkpoint where progress is discussed against the plan for the week. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. 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. 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. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. The organisation has historically promoted from within for a majority of its senior and lead openings. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Compensation includes standard statutory benefits along with performance-linked variable pay. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. High performers in this role typically move into a broader ownership scope within 18-24 months. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. The package is structured with a fixed component, performance bonus, and standard health coverage. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.