Job Description
This position calls for an Advanced Neural Network Engineer who can take ownership of core responsibilities within our Deep Learning team. This is a mid level opening based out of Lucknow, offered on a full-time basis.
The ideal candidate holds M.Tech (Machine Learning) and brings roughly 4 years of hands-on exposure to deep learning. Day-to-day, the work draws heavily on Deep Learning, Python, Cloud Platforms (AWS/GCP), Data Preprocessing, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 11.0-31.9 LPA, in line with market standards for mid level roles within machine learning.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
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. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Learning and certification support is available for tools and frameworks directly relevant to the role.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. Compensation includes standard statutory benefits along with performance-linked variable pay.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
If your background aligns with the above and you're looking for your next step in Deep Learning, we'd like to hear from you.
The ideal candidate holds M.Tech (Machine Learning) and brings roughly 4 years of hands-on exposure to deep learning. Day-to-day, the work draws heavily on Deep Learning, Python, Cloud Platforms (AWS/GCP), Data Preprocessing, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 11.0-31.9 LPA, in line with market standards for mid level roles within machine learning.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
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. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Learning and certification support is available for tools and frameworks directly relevant to the role.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. Compensation includes standard statutory benefits along with performance-linked variable pay.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
If your background aligns with the above and you're looking for your next step in Deep Learning, we'd like to hear from you.