Job Description
Position: ML Platform Engineer
Function: MLOps
Industry: Machine Learning
Grade: mid level
Location: Lucknow
Employment Type: Full-time
Compensation: INR 22.5-46.9 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with mlops, in accordance with the standards and processes laid down by Machine Learning.
Minimum Qualification: M.Sc (Data Science)
Minimum Experience: 3 years
Core Competencies Required: MLOps, Data Preprocessing, Computer Vision/NLP Basics, Cloud Platforms (AWS/GCP), Deep Learning, Python
Further Information:
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. 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. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. The organisation has historically promoted from within for a majority of its senior and lead openings. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. 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. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Compensation includes standard statutory benefits along with performance-linked variable pay. Internal job postings are open to employees who've completed a minimum tenure in their current role. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Relocation assistance may be extended for candidates moving from a different city, subject to approval. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. References may be requested closer to the offer stage rather than at the start of the process. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The package is structured with a fixed component, performance bonus, and standard health coverage. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Most days include at least one review checkpoint where progress is discussed against the plan for the week. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Function: MLOps
Industry: Machine Learning
Grade: mid level
Location: Lucknow
Employment Type: Full-time
Compensation: INR 22.5-46.9 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with mlops, in accordance with the standards and processes laid down by Machine Learning.
Minimum Qualification: M.Sc (Data Science)
Minimum Experience: 3 years
Core Competencies Required: MLOps, Data Preprocessing, Computer Vision/NLP Basics, Cloud Platforms (AWS/GCP), Deep Learning, Python
Further Information:
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. 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. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. The organisation has historically promoted from within for a majority of its senior and lead openings. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. 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. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Compensation includes standard statutory benefits along with performance-linked variable pay. Internal job postings are open to employees who've completed a minimum tenure in their current role. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Relocation assistance may be extended for candidates moving from a different city, subject to approval. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. References may be requested closer to the offer stage rather than at the start of the process. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The package is structured with a fixed component, performance bonus, and standard health coverage. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Most days include at least one review checkpoint where progress is discussed against the plan for the week. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.