Job Description
AI Risk & Compliance Specialist | Bengaluru | INR 22.0-39.9 LPA
AI-driven Risk Management role, mid level, hybrid.
Need: M.Sc (Data Science), 5+ yrs.
Core skills: Model Deployment (MLOps), Deep Learning, TensorFlow/PyTorch, Data Preprocessing, Machine Learning.
If this fits your profile in ai-driven risk management, apply now.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. High performers in this role typically move into a broader ownership scope within 18-24 months.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The organisation has historically promoted from within for a majority of its senior and lead openings. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. 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. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. 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. Learning and certification support is available for tools and frameworks directly relevant to the role. Internal job postings are open to employees who've completed a minimum tenure in their current role.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
AI-driven Risk Management role, mid level, hybrid.
Need: M.Sc (Data Science), 5+ yrs.
Core skills: Model Deployment (MLOps), Deep Learning, TensorFlow/PyTorch, Data Preprocessing, Machine Learning.
If this fits your profile in ai-driven risk management, apply now.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. High performers in this role typically move into a broader ownership scope within 18-24 months.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The organisation has historically promoted from within for a majority of its senior and lead openings. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. 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. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. 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. Learning and certification support is available for tools and frameworks directly relevant to the role. Internal job postings are open to employees who've completed a minimum tenure in their current role.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.