Job Description
## Machine Learning Security Engineer – Junior
**Department:** AI Security & Privacy | **Industry:** Artificial Intelligence (AI)
**Location:** Bhubaneswar | **Job Type:** Full-time (WFH) | **CTC:** INR 7.7-24.3 LPA
### Role Overview
This position calls for a Machine Learning Security Engineer – Junior who can take ownership of core responsibilities within our AI Security & Privacy team. The role is positioned at the junior level and reports into the broader AI Security & Privacy charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to ai security & privacy.
- Apply working knowledge of Python and AI Security to daily execution.
- Coordinate with cross-functional stakeholders within Artificial Intelligence (AI).
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- B.Tech (CS/AI) or equivalent qualification.
- 2 years of relevant experience (junior level).
- Working proficiency in: Python, AI Security, Deep Learning, Privacy, Cloud Platforms (AWS/GCP/Azure), Statistical Modelling.
### Additional Notes
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. 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. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. There is a defined internal mobility path for people who want to specialise deeper or move into people management. The organisation has historically promoted from within for a majority of its senior and lead openings. 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. The package is structured with a fixed component, performance bonus, and standard health coverage. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
**Department:** AI Security & Privacy | **Industry:** Artificial Intelligence (AI)
**Location:** Bhubaneswar | **Job Type:** Full-time (WFH) | **CTC:** INR 7.7-24.3 LPA
### Role Overview
This position calls for a Machine Learning Security Engineer – Junior who can take ownership of core responsibilities within our AI Security & Privacy team. The role is positioned at the junior level and reports into the broader AI Security & Privacy charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to ai security & privacy.
- Apply working knowledge of Python and AI Security to daily execution.
- Coordinate with cross-functional stakeholders within Artificial Intelligence (AI).
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- B.Tech (CS/AI) or equivalent qualification.
- 2 years of relevant experience (junior level).
- Working proficiency in: Python, AI Security, Deep Learning, Privacy, Cloud Platforms (AWS/GCP/Azure), Statistical Modelling.
### Additional Notes
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. 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. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. There is a defined internal mobility path for people who want to specialise deeper or move into people management. The organisation has historically promoted from within for a majority of its senior and lead openings. 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. The package is structured with a fixed component, performance bonus, and standard health coverage. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.