Job Description
Machine Learning is looking for an experienced Advanced AI Threat Intelligence Architect to take ownership of the AI for Cybersecurity 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 14 years of progressively senior experience, holding M.Sc (Data Science), with a demonstrated track record across Python, Data Preprocessing, TensorFlow/PyTorch, Deep Learning, Model Evaluation & Tuning. 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 Mumbai on a full-time arrangement. Compensation is benchmarked at INR 11.5-49.8 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 for cybersecurity.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
High performers in this role typically move into a broader ownership scope within 18-24 months. References may be requested closer to the offer stage rather than at the start of the process.
Compensation includes standard statutory benefits along with performance-linked variable pay. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. 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. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
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.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Internal job postings are open to employees who've completed a minimum tenure in their current role. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. The organisation has historically promoted from within for a majority of its senior and lead openings. 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 team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. 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. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
The successful candidate will bring approximately 14 years of progressively senior experience, holding M.Sc (Data Science), with a demonstrated track record across Python, Data Preprocessing, TensorFlow/PyTorch, Deep Learning, Model Evaluation & Tuning. 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 Mumbai on a full-time arrangement. Compensation is benchmarked at INR 11.5-49.8 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 for cybersecurity.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
High performers in this role typically move into a broader ownership scope within 18-24 months. References may be requested closer to the offer stage rather than at the start of the process.
Compensation includes standard statutory benefits along with performance-linked variable pay. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. 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. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
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.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Internal job postings are open to employees who've completed a minimum tenure in their current role. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. The organisation has historically promoted from within for a majority of its senior and lead openings. 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 team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. 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. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.