Job Description
Director – AI Operations & Reliability | Coimbatore | INR 41.7-63.0 LPA
AI Operations (AIOps) role, senior level, full-time.
Need: M.Sc (Data Science), 11+ yrs.
Core skills: TensorFlow/PyTorch, Deep Learning, Computer Vision, AI Operations (AIOps), Python.
If this fits your profile in ai operations (aiops), apply now.
Internal job postings are open to employees who've completed a minimum tenure in their current role. High performers in this role typically move into a broader ownership scope within 18-24 months.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. 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.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. The package is structured with a fixed component, performance bonus, and standard health coverage. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Learning and certification support is available for tools and frameworks directly relevant to the role.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. References may be requested closer to the offer stage rather than at the start of the 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. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
AI Operations (AIOps) role, senior level, full-time.
Need: M.Sc (Data Science), 11+ yrs.
Core skills: TensorFlow/PyTorch, Deep Learning, Computer Vision, AI Operations (AIOps), Python.
If this fits your profile in ai operations (aiops), apply now.
Internal job postings are open to employees who've completed a minimum tenure in their current role. High performers in this role typically move into a broader ownership scope within 18-24 months.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. 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.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. The package is structured with a fixed component, performance bonus, and standard health coverage. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Learning and certification support is available for tools and frameworks directly relevant to the role.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. References may be requested closer to the offer stage rather than at the start of the 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. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Most days include at least one review checkpoint where progress is discussed against the plan for the week.