Job Description
Position: AI Operations Analyst – Mid Level
Function: AI Operations (AIOps)
Industry: Artificial Intelligence (AI)
Grade: mid level
Location: Gurugram
Employment Type: Contract
Compensation: INR 19.0-35.6 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with ai operations (aiops), in accordance with the standards and processes laid down by Artificial Intelligence (AI).
Minimum Qualification: M.Sc (Data Science)
Minimum Experience: 5 years
Core Competencies Required: Computer Vision, AI Operations (AIOps), TensorFlow/PyTorch, Python, Neural Network Architectures, Natural Language Processing, Model Deployment (MLOps), Deep Learning
Further Information:
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. References may be requested closer to the offer stage rather than at the start of the process. There is a defined internal mobility path for people who want to specialise deeper or move into people management. The next logical step from this position is a senior or lead-track role within the same function. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The package is structured with a fixed component, performance bonus, and standard health coverage. 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. 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. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. The organisation has historically promoted from within for a majority of its senior and lead openings. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. High performers in this role typically move into a broader ownership scope within 18-24 months. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Interested candidates should be prepared to walk through relevant past work during the interview process. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
Function: AI Operations (AIOps)
Industry: Artificial Intelligence (AI)
Grade: mid level
Location: Gurugram
Employment Type: Contract
Compensation: INR 19.0-35.6 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with ai operations (aiops), in accordance with the standards and processes laid down by Artificial Intelligence (AI).
Minimum Qualification: M.Sc (Data Science)
Minimum Experience: 5 years
Core Competencies Required: Computer Vision, AI Operations (AIOps), TensorFlow/PyTorch, Python, Neural Network Architectures, Natural Language Processing, Model Deployment (MLOps), Deep Learning
Further Information:
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. References may be requested closer to the offer stage rather than at the start of the process. There is a defined internal mobility path for people who want to specialise deeper or move into people management. The next logical step from this position is a senior or lead-track role within the same function. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The package is structured with a fixed component, performance bonus, and standard health coverage. 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. 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. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. The organisation has historically promoted from within for a majority of its senior and lead openings. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. High performers in this role typically move into a broader ownership scope within 18-24 months. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Interested candidates should be prepared to walk through relevant past work during the interview process. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.