Job Description
Machine Learning is looking for an experienced Machine Learning Systems Engineer to take ownership of the Machine Learning Engineering 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.Tech (Machine Learning), with a demonstrated track record across TensorFlow/PyTorch, Machine Learning Engineering, Computer Vision/NLP Basics, Statistical Modelling, Feature Engineering. 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 Delhi NCR on a full-time arrangement. Compensation is benchmarked at INR 11.8-33.4 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 machine learning engineering.
Internal job postings are open to employees who've completed a minimum tenure in their current role. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
References may be requested closer to the offer stage rather than at the start of the process. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Compensation includes standard statutory benefits along with performance-linked variable pay. The organisation has historically promoted from within for a majority of its senior and lead openings.
High performers in this role typically move into a broader ownership scope within 18-24 months. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
The successful candidate will bring approximately 7 years of progressively senior experience, holding M.Tech (Machine Learning), with a demonstrated track record across TensorFlow/PyTorch, Machine Learning Engineering, Computer Vision/NLP Basics, Statistical Modelling, Feature Engineering. 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 Delhi NCR on a full-time arrangement. Compensation is benchmarked at INR 11.8-33.4 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 machine learning engineering.
Internal job postings are open to employees who've completed a minimum tenure in their current role. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
References may be requested closer to the offer stage rather than at the start of the process. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Compensation includes standard statutory benefits along with performance-linked variable pay. The organisation has historically promoted from within for a majority of its senior and lead openings.
High performers in this role typically move into a broader ownership scope within 18-24 months. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.