Job Description
Machine Learning is looking for an experienced Neural AI Systems Engineer to take ownership of the Deep Learning charter at a mid level. This is a role for someone who has already operated at scale and is comfortable setting direction rather than simply following one.
The successful candidate will bring approximately 7 years of progressively senior experience, holding M.Sc (Data Science), with a demonstrated track record across Statistical Modelling, Deep Learning, Python, Cloud Platforms (AWS/GCP), TensorFlow/PyTorch. Beyond individual capability, this role expects the person to mentor junior team members and represent the function in cross-departmental discussions.
Reporting relationships will be defined based on the final scope agreed at offer stage, and the role is based out of Pune on a contract arrangement. Compensation is benchmarked at INR 18.3-30.3 LPA, reflecting the seniority and scope of the position.
Success in this role will be measured less by task completion and more by the quality of judgement applied to ambiguous, high-stakes situations within deep learning.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. 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. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Compensation includes standard statutory benefits along with performance-linked variable pay. 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. Interested candidates should be prepared to walk through relevant past work during the interview process. Internal job postings are open to employees who've completed a minimum tenure in their current role.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. 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.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. The package is structured with a fixed component, performance bonus, and standard health coverage.
References may be requested closer to the offer stage rather than at the start of the process. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
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.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. The next logical step from this position is a senior or lead-track role within the same function.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Relocation assistance may be extended for candidates moving from a different city, subject to approval. The organisation has historically promoted from within for a majority of its senior and lead openings.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Learning and certification support is available for tools and frameworks directly relevant to the role.
The successful candidate will bring approximately 7 years of progressively senior experience, holding M.Sc (Data Science), with a demonstrated track record across Statistical Modelling, Deep Learning, Python, Cloud Platforms (AWS/GCP), TensorFlow/PyTorch. Beyond individual capability, this role expects the person to mentor junior team members and represent the function in cross-departmental discussions.
Reporting relationships will be defined based on the final scope agreed at offer stage, and the role is based out of Pune on a contract arrangement. Compensation is benchmarked at INR 18.3-30.3 LPA, reflecting the seniority and scope of the position.
Success in this role will be measured less by task completion and more by the quality of judgement applied to ambiguous, high-stakes situations within deep learning.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. 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. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Compensation includes standard statutory benefits along with performance-linked variable pay. 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. Interested candidates should be prepared to walk through relevant past work during the interview process. Internal job postings are open to employees who've completed a minimum tenure in their current role.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. 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.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. The package is structured with a fixed component, performance bonus, and standard health coverage.
References may be requested closer to the offer stage rather than at the start of the process. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
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.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. The next logical step from this position is a senior or lead-track role within the same function.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Relocation assistance may be extended for candidates moving from a different city, subject to approval. The organisation has historically promoted from within for a majority of its senior and lead openings.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Learning and certification support is available for tools and frameworks directly relevant to the role.