Job Description
Artificial Intelligence (AI) is looking for an experienced Director – AI Learning Initiatives to take ownership of the AI Training & Upskilling Programs 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 12 years of progressively senior experience, holding M.Sc (Data Science), with a demonstrated track record across Upskilling Programs, Statistical Modelling, Neural Network Architectures, Natural Language Processing, TensorFlow/PyTorch. 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 Chennai on a full-time arrangement. Compensation is benchmarked at INR 15.7-74.7 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 ai training & upskilling programs.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Interested candidates should be prepared to walk through relevant past work during the interview process.
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. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Compensation includes standard statutory benefits along with performance-linked variable pay.
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.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. High performers in this role typically move into a broader ownership scope within 18-24 months.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
The successful candidate will bring approximately 12 years of progressively senior experience, holding M.Sc (Data Science), with a demonstrated track record across Upskilling Programs, Statistical Modelling, Neural Network Architectures, Natural Language Processing, TensorFlow/PyTorch. 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 Chennai on a full-time arrangement. Compensation is benchmarked at INR 15.7-74.7 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 ai training & upskilling programs.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Interested candidates should be prepared to walk through relevant past work during the interview process.
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. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Compensation includes standard statutory benefits along with performance-linked variable pay.
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.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. High performers in this role typically move into a broader ownership scope within 18-24 months.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.