Job Description
## Director – AI R&D
**Department:** AI Research & Development | **Industry:** Artificial Intelligence (AI)
**Location:** Hybrid - Bengaluru | **Job Type:** Full-time | **CTC:** INR 18.0-52.4 LPA
### Role Overview
The organisation is seeking a qualified Director – AI R&D to support ongoing initiatives in 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 Neural Network Architectures and Model Deployment (MLOps) 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.Sc (Data Science) or equivalent qualification.
- 16 years of relevant experience (senior level).
- Working proficiency in: Neural Network Architectures, Model Deployment (MLOps), Natural Language Processing, TensorFlow/PyTorch, Python, AI Research, Development.
### Additional Notes
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Learning and certification support is available for tools and frameworks directly relevant to the role. Compensation includes standard statutory benefits along with performance-linked variable pay. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Most days include at least one review checkpoint where progress is discussed against the plan for the week. The package is structured with a fixed component, performance bonus, and standard health coverage. 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. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Relocation assistance may be extended for candidates moving from a different city, subject to approval. 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. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
**Department:** AI Research & Development | **Industry:** Artificial Intelligence (AI)
**Location:** Hybrid - Bengaluru | **Job Type:** Full-time | **CTC:** INR 18.0-52.4 LPA
### Role Overview
The organisation is seeking a qualified Director – AI R&D to support ongoing initiatives in 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 Neural Network Architectures and Model Deployment (MLOps) 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.Sc (Data Science) or equivalent qualification.
- 16 years of relevant experience (senior level).
- Working proficiency in: Neural Network Architectures, Model Deployment (MLOps), Natural Language Processing, TensorFlow/PyTorch, Python, AI Research, Development.
### Additional Notes
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Learning and certification support is available for tools and frameworks directly relevant to the role. Compensation includes standard statutory benefits along with performance-linked variable pay. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Most days include at least one review checkpoint where progress is discussed against the plan for the week. The package is structured with a fixed component, performance bonus, and standard health coverage. 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. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Relocation assistance may be extended for candidates moving from a different city, subject to approval. 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. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.