Job Description
Join us as a Machine Learning DevOps Engineer and help us push Machine Learning Engineering forward within Application Development / Software Applications.
You'll be working out of Mumbai (full-time), and honestly, the day-to-day is going to revolve around CI/CD Pipelines and Machine Learning Engineering. 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 BCA and somewhere around 4 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 3.3-29.7 LPA - fair for the mid level band and open to discussion based on what you bring.
The organisation has historically promoted from within for a majority of its senior and lead openings. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Learning and certification support is available for tools and frameworks directly relevant to the role. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Interested candidates should be prepared to walk through relevant past work during the interview process.
References may be requested closer to the offer stage rather than at the start of the process. Relocation assistance may be extended for candidates moving from a different city, subject to approval. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Compensation includes standard statutory benefits along with performance-linked variable pay. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
You'll be working out of Mumbai (full-time), and honestly, the day-to-day is going to revolve around CI/CD Pipelines and Machine Learning Engineering. 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 BCA and somewhere around 4 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 3.3-29.7 LPA - fair for the mid level band and open to discussion based on what you bring.
The organisation has historically promoted from within for a majority of its senior and lead openings. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Learning and certification support is available for tools and frameworks directly relevant to the role. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Interested candidates should be prepared to walk through relevant past work during the interview process.
References may be requested closer to the offer stage rather than at the start of the process. Relocation assistance may be extended for candidates moving from a different city, subject to approval. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Compensation includes standard statutory benefits along with performance-linked variable pay. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.