Job Description
## AI Regulatory Compliance Engineer
**Department:** AI Policy & Compliance | **Industry:** Machine Learning
**Location:** Hybrid - Pune | **Job Type:** Full-time | **CTC:** INR 22.8-40.6 LPA
### Role Overview
The organisation is seeking a qualified AI Regulatory Compliance Engineer to support ongoing initiatives in AI Policy & Compliance. The role is positioned at the mid 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 Python and Machine Learning Algorithms 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.
- 3 years of relevant experience (mid level).
- Working proficiency in: Python, Machine Learning Algorithms, Computer Vision/NLP Basics, Data Preprocessing, AI Policy, Cloud Platforms (AWS/GCP), Compliance.
### Additional Notes
Compensation includes standard statutory benefits along with performance-linked variable pay. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. 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. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
**Department:** AI Policy & Compliance | **Industry:** Machine Learning
**Location:** Hybrid - Pune | **Job Type:** Full-time | **CTC:** INR 22.8-40.6 LPA
### Role Overview
The organisation is seeking a qualified AI Regulatory Compliance Engineer to support ongoing initiatives in AI Policy & Compliance. The role is positioned at the mid 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 Python and Machine Learning Algorithms 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.
- 3 years of relevant experience (mid level).
- Working proficiency in: Python, Machine Learning Algorithms, Computer Vision/NLP Basics, Data Preprocessing, AI Policy, Cloud Platforms (AWS/GCP), Compliance.
### Additional Notes
Compensation includes standard statutory benefits along with performance-linked variable pay. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. 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. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.