Job Description
**AI Workflow Support Engineer** | Chennai | Internship | INR 5.7-21.2 LPA
**About the role:**
- Position within AI Operations (AIOps), under the Artificial Intelligence (AI) vertical
- Level: junior level
- Reports to the functional head for AI Operations (AIOps)
**What you'll do:**
- Handle core ai operations (aiops) activities on a day-to-day basis
- Use Statistical Modelling 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:**
- Statistical Modelling
- AI Operations (AIOps)
- TensorFlow/PyTorch
- Neural Network Architectures
- Python
- Data Preprocessing
- M.Tech (AI/ML)
- 0+ years of relevant experience
**Good to know:**
- In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
- Internal job postings are open to employees who've completed a minimum tenure in their current role. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
- The package is structured with a fixed component, performance bonus, and standard health coverage. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
- 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.
- Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
- Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
**About the role:**
- Position within AI Operations (AIOps), under the Artificial Intelligence (AI) vertical
- Level: junior level
- Reports to the functional head for AI Operations (AIOps)
**What you'll do:**
- Handle core ai operations (aiops) activities on a day-to-day basis
- Use Statistical Modelling 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:**
- Statistical Modelling
- AI Operations (AIOps)
- TensorFlow/PyTorch
- Neural Network Architectures
- Python
- Data Preprocessing
- M.Tech (AI/ML)
- 0+ years of relevant experience
**Good to know:**
- In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
- Internal job postings are open to employees who've completed a minimum tenure in their current role. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
- The package is structured with a fixed component, performance bonus, and standard health coverage. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
- 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.
- Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
- Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.