Job Description
**AI Cyber Defense Assistant** | Hybrid - Bengaluru | Full-time | INR 4.7-19.0 LPA
**About the role:**
- Position within AI for Cybersecurity, under the Machine Learning vertical
- Level: junior level
- Reports to the functional head for AI for Cybersecurity
**What you'll do:**
- Handle core ai for cybersecurity activities on a day-to-day basis
- Use Data Preprocessing regularly as part of core deliverables
- Work closely with adjacent teams to align priorities
- Track progress against agreed timelines and escalate issues proactively
**What you'll need:**
- Data Preprocessing
- AI for Cybersecurity
- Python
- Cloud Platforms (AWS/GCP)
- M.Tech (Machine Learning)
- 2+ years of relevant experience
**Good to know:**
- New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
- Most days include at least one review checkpoint where progress is discussed against the plan for the week. Relocation assistance may be extended for candidates moving from a different city, subject to approval. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
- The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. References may be requested closer to the offer stage rather than at the start of the process.
- Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
- Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Internal job postings are open to employees who've completed a minimum tenure in their current role.
- 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 organisation has historically promoted from within for a majority of its senior and lead openings.
**About the role:**
- Position within AI for Cybersecurity, under the Machine Learning vertical
- Level: junior level
- Reports to the functional head for AI for Cybersecurity
**What you'll do:**
- Handle core ai for cybersecurity activities on a day-to-day basis
- Use Data Preprocessing regularly as part of core deliverables
- Work closely with adjacent teams to align priorities
- Track progress against agreed timelines and escalate issues proactively
**What you'll need:**
- Data Preprocessing
- AI for Cybersecurity
- Python
- Cloud Platforms (AWS/GCP)
- M.Tech (Machine Learning)
- 2+ years of relevant experience
**Good to know:**
- New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
- Most days include at least one review checkpoint where progress is discussed against the plan for the week. Relocation assistance may be extended for candidates moving from a different city, subject to approval. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
- The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. References may be requested closer to the offer stage rather than at the start of the process.
- Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
- Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Internal job postings are open to employees who've completed a minimum tenure in their current role.
- 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 organisation has historically promoted from within for a majority of its senior and lead openings.