Job Description
Looking for a Machine Learning Operations Engineer who's genuinely interested in Machine Learning Engineering and wants to make an impact from day one.
You'll be working out of Noida (full-time), and honestly, the day-to-day is going to revolve around Feature Engineering and Statistical Modelling. We're not looking for someone who just ticks boxes - we want someone who actually cares about machine learning engineering.
On paper, we'd expect M.Tech (Machine Learning) and somewhere around 3 years of experience, but we're just as interested in how you think as in what's on your resume.
Pay-wise, we're offering INR 24.7-53.7 LPA - fair for the mid level band and open to discussion based on what you bring.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. 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. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
Learning and certification support is available for tools and frameworks directly relevant to the role. Compensation includes standard statutory benefits along with performance-linked variable pay.
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. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
Internal job postings are open to employees who've completed a minimum tenure in their current role. There is a defined internal mobility path for people who want to specialise deeper or move into people management. The organisation has historically promoted from within for a majority of its senior and lead openings.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. High performers in this role typically move into a broader ownership scope within 18-24 months.
References may be requested closer to the offer stage rather than at the start of the process. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
You'll be working out of Noida (full-time), and honestly, the day-to-day is going to revolve around Feature Engineering and Statistical Modelling. We're not looking for someone who just ticks boxes - we want someone who actually cares about machine learning engineering.
On paper, we'd expect M.Tech (Machine Learning) and somewhere around 3 years of experience, but we're just as interested in how you think as in what's on your resume.
Pay-wise, we're offering INR 24.7-53.7 LPA - fair for the mid level band and open to discussion based on what you bring.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. 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. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
Learning and certification support is available for tools and frameworks directly relevant to the role. Compensation includes standard statutory benefits along with performance-linked variable pay.
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. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
Internal job postings are open to employees who've completed a minimum tenure in their current role. There is a defined internal mobility path for people who want to specialise deeper or move into people management. The organisation has historically promoted from within for a majority of its senior and lead openings.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. High performers in this role typically move into a broader ownership scope within 18-24 months.
References may be requested closer to the offer stage rather than at the start of the process. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.