Job Description
Machine Learning is looking for an experienced Generative AI Research Engineer to take ownership of the Generative AI 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 3 years of progressively senior experience, holding M.Sc (Data Science), with a demonstrated track record across Python, Model Evaluation & Tuning, Generative AI, MLOps, 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 full-time arrangement. Compensation is benchmarked at INR 9.1-31.5 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 generative ai.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The package is structured with a fixed component, performance bonus, and standard health coverage.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Compensation includes standard statutory benefits along with performance-linked variable pay.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
References may be requested closer to the offer stage rather than at the start of the process. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
The successful candidate will bring approximately 3 years of progressively senior experience, holding M.Sc (Data Science), with a demonstrated track record across Python, Model Evaluation & Tuning, Generative AI, MLOps, 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 full-time arrangement. Compensation is benchmarked at INR 9.1-31.5 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 generative ai.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The package is structured with a fixed component, performance bonus, and standard health coverage.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Compensation includes standard statutory benefits along with performance-linked variable pay.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
References may be requested closer to the offer stage rather than at the start of the process. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.