Job Description
Machine Learning is looking for an experienced AI Regulatory Strategy Director to take ownership of the AI Policy & Compliance 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 15 years of progressively senior experience, holding M.Sc (Data Science), with a demonstrated track record across Computer Vision/NLP Basics, MLOps, Machine Learning Algorithms, Statistical Modelling, Compliance. 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 Bengaluru on a full-time arrangement. Compensation is benchmarked at INR 9.5-55.0 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 policy & compliance.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. 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.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Internal job postings are open to employees who've completed a minimum tenure in their current role.
The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
Learning and certification support is available for tools and frameworks directly relevant to the role. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
The successful candidate will bring approximately 15 years of progressively senior experience, holding M.Sc (Data Science), with a demonstrated track record across Computer Vision/NLP Basics, MLOps, Machine Learning Algorithms, Statistical Modelling, Compliance. 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 Bengaluru on a full-time arrangement. Compensation is benchmarked at INR 9.5-55.0 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 policy & compliance.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. 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.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Internal job postings are open to employees who've completed a minimum tenure in their current role.
The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
Learning and certification support is available for tools and frameworks directly relevant to the role. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.