Job Description
The organisation is seeking a qualified MLOps Systems Architect to support ongoing initiatives in MLOps. This is a senior level opening based out of Bengaluru, offered on a full-time basis.
The ideal candidate holds M.Tech (Machine Learning) and brings roughly 15 years of hands-on exposure to mlops. Day-to-day, the work draws heavily on Cloud Platforms (AWS/GCP), MLOps, Computer Vision/NLP Basics, Statistical Modelling, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 12.4-73.4 LPA, in line with market standards for senior level roles within machine learning.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
Mornings are usually spent on planning and status reviews, while the rest of the day is given over to hands-on delivery and problem-solving. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Internal job postings are open to employees who've completed a minimum tenure in their current role.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Interested candidates should be prepared to walk through relevant past work during the interview process.
The next logical step from this position is a senior or lead-track role within the same function. High performers in this role typically move into a broader ownership scope within 18-24 months. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. Compensation includes standard statutory benefits along with performance-linked variable pay.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
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 environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The organisation has historically promoted from within for a majority of its senior and lead openings.
This role offers a genuine opportunity to build depth in MLOps while working alongside an experienced team.
The ideal candidate holds M.Tech (Machine Learning) and brings roughly 15 years of hands-on exposure to mlops. Day-to-day, the work draws heavily on Cloud Platforms (AWS/GCP), MLOps, Computer Vision/NLP Basics, Statistical Modelling, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 12.4-73.4 LPA, in line with market standards for senior level roles within machine learning.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
Mornings are usually spent on planning and status reviews, while the rest of the day is given over to hands-on delivery and problem-solving. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Internal job postings are open to employees who've completed a minimum tenure in their current role.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Interested candidates should be prepared to walk through relevant past work during the interview process.
The next logical step from this position is a senior or lead-track role within the same function. High performers in this role typically move into a broader ownership scope within 18-24 months. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. Compensation includes standard statutory benefits along with performance-linked variable pay.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
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 environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The organisation has historically promoted from within for a majority of its senior and lead openings.
This role offers a genuine opportunity to build depth in MLOps while working alongside an experienced team.