Job Description
## AI Regulatory Documentation Analyst
**Department:** AI Policy & Compliance | **Industry:** Machine Learning
**Location:** Kolkata | **Job Type:** Contract | **CTC:** INR 4.1-17.3 LPA
### Role Overview
An opening exists for an AI Regulatory Documentation Analyst to join the Machine Learning vertical, focused on AI Policy & Compliance. The role is positioned at the junior level and reports into the broader AI Policy & Compliance charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to ai policy & compliance.
- Apply working knowledge of TensorFlow/PyTorch and Feature Engineering to daily execution.
- Coordinate with cross-functional stakeholders within Machine Learning.
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Tech (Machine Learning) or equivalent qualification.
- 2 years of relevant experience (junior level).
- Working proficiency in: TensorFlow/PyTorch, Feature Engineering, Compliance, AI Policy, Python, Deep Learning.
### Additional Notes
References may be requested closer to the offer stage rather than at the start of the process. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Learning and certification support is available for tools and frameworks directly relevant to the role. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Interested candidates should be prepared to walk through relevant past work during the interview process. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. 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. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
**Department:** AI Policy & Compliance | **Industry:** Machine Learning
**Location:** Kolkata | **Job Type:** Contract | **CTC:** INR 4.1-17.3 LPA
### Role Overview
An opening exists for an AI Regulatory Documentation Analyst to join the Machine Learning vertical, focused on AI Policy & Compliance. The role is positioned at the junior level and reports into the broader AI Policy & Compliance charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to ai policy & compliance.
- Apply working knowledge of TensorFlow/PyTorch and Feature Engineering to daily execution.
- Coordinate with cross-functional stakeholders within Machine Learning.
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Tech (Machine Learning) or equivalent qualification.
- 2 years of relevant experience (junior level).
- Working proficiency in: TensorFlow/PyTorch, Feature Engineering, Compliance, AI Policy, Python, Deep Learning.
### Additional Notes
References may be requested closer to the offer stage rather than at the start of the process. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Learning and certification support is available for tools and frameworks directly relevant to the role. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Interested candidates should be prepared to walk through relevant past work during the interview process. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. 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. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.