Job Description
Looking for a Machine Learning Pipeline Engineer who's genuinely interested in Machine Learning Engineering and wants to make an impact from day one.
You'll be working out of Coimbatore (hybrid), and honestly, the day-to-day is going to revolve around Feature Engineering and MLOps. 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 7 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 19.9-30.4 LPA - fair for the mid level band and open to discussion based on what you bring.
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. Internal job postings are open to employees who've completed a minimum tenure in their current role.
Learning and certification support is available for tools and frameworks directly relevant to the role. The package is structured with a fixed component, performance bonus, and standard health coverage. Compensation includes standard statutory benefits along with performance-linked variable pay.
Interested candidates should be prepared to walk through relevant past work during the interview process. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
High performers in this role typically move into a broader ownership scope within 18-24 months. Most days include at least one review checkpoint where progress is discussed against the plan for the week. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. References may be requested closer to the offer stage rather than at the start of the process. The next logical step from this position is a senior or lead-track role within the same function.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. 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 Coimbatore (hybrid), and honestly, the day-to-day is going to revolve around Feature Engineering and MLOps. 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 7 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 19.9-30.4 LPA - fair for the mid level band and open to discussion based on what you bring.
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. Internal job postings are open to employees who've completed a minimum tenure in their current role.
Learning and certification support is available for tools and frameworks directly relevant to the role. The package is structured with a fixed component, performance bonus, and standard health coverage. Compensation includes standard statutory benefits along with performance-linked variable pay.
Interested candidates should be prepared to walk through relevant past work during the interview process. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
High performers in this role typically move into a broader ownership scope within 18-24 months. Most days include at least one review checkpoint where progress is discussed against the plan for the week. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. References may be requested closer to the offer stage rather than at the start of the process. The next logical step from this position is a senior or lead-track role within the same function.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.