Job Description
An opening exists for an AI Strategy and Innovation Director to join the Machine Learning vertical, focused on AI Strategy & Business Integration. This is a senior level opening based out of Kolkata, offered on a full-time basis.
The ideal candidate holds Ph.D (ML/AI) and brings roughly 15 years of hands-on exposure to ai strategy & business integration. Day-to-day, the work draws heavily on Computer Vision/NLP Basics, AI Strategy, Data Preprocessing, Feature Engineering, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 9.7-73.9 LPA, in line with market standards for senior level roles within machine learning.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. 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 team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. 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. References may be requested closer to the offer stage rather than at the start of the process.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Interested candidates should be prepared to walk through relevant past work during the interview process.
Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
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. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
This is a good fit for someone who wants real ownership rather than a purely execution-only role.
The ideal candidate holds Ph.D (ML/AI) and brings roughly 15 years of hands-on exposure to ai strategy & business integration. Day-to-day, the work draws heavily on Computer Vision/NLP Basics, AI Strategy, Data Preprocessing, Feature Engineering, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 9.7-73.9 LPA, in line with market standards for senior level roles within machine learning.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. 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 team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. 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. References may be requested closer to the offer stage rather than at the start of the process.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Interested candidates should be prepared to walk through relevant past work during the interview process.
Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
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. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
This is a good fit for someone who wants real ownership rather than a purely execution-only role.