Job Description
This position calls for an AI Product Integration Assistant who can take ownership of core responsibilities within our AI Product Management team. This is a junior level opening based out of Bengaluru, offered on a internship basis.
The ideal candidate holds M.Tech (Machine Learning) and brings roughly 2 years of hands-on exposure to ai product management. Day-to-day, the work draws heavily on Feature Engineering, Model Evaluation & Tuning, Deep Learning, Computer Vision/NLP Basics, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 8.7-14.1 LPA, in line with market standards for junior level roles within machine learning.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. References may be requested closer to the offer stage rather than at the start of the process. The next logical step from this position is a senior or lead-track role within the same function.
We value consistency and follow-through more than flashy credentials - if that matches how you work, apply in.
The ideal candidate holds M.Tech (Machine Learning) and brings roughly 2 years of hands-on exposure to ai product management. Day-to-day, the work draws heavily on Feature Engineering, Model Evaluation & Tuning, Deep Learning, Computer Vision/NLP Basics, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 8.7-14.1 LPA, in line with market standards for junior level roles within machine learning.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. References may be requested closer to the offer stage rather than at the start of the process. The next logical step from this position is a senior or lead-track role within the same function.
We value consistency and follow-through more than flashy credentials - if that matches how you work, apply in.