Job Description
Position: Machine Learning Developer
Function: Machine Learning Engineering
Industry: Analytics / Data Analytics
Grade: mid level
Location: Chandigarh
Employment Type: Full-time
Compensation: INR 7.8-23.8 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with machine learning engineering, in accordance with the standards and processes laid down by Analytics / Data Analytics.
Minimum Qualification: B.Sc (Statistics)
Minimum Experience: 3 years
Core Competencies Required: Machine Learning Engineering, SQL, Business Intelligence, Statistical Modelling, Predictive Analytics
Further Information:
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. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The next logical step from this position is a senior or lead-track role within the same function. Most days include at least one review checkpoint where progress is discussed against the plan for the week. 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. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Interested candidates should be prepared to walk through relevant past work during the interview process. Learning and certification support is available for tools and frameworks directly relevant to the role. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. The organisation has historically promoted from within for a majority of its senior and lead openings. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. 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. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Compensation includes standard statutory benefits along with performance-linked variable pay. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
Function: Machine Learning Engineering
Industry: Analytics / Data Analytics
Grade: mid level
Location: Chandigarh
Employment Type: Full-time
Compensation: INR 7.8-23.8 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with machine learning engineering, in accordance with the standards and processes laid down by Analytics / Data Analytics.
Minimum Qualification: B.Sc (Statistics)
Minimum Experience: 3 years
Core Competencies Required: Machine Learning Engineering, SQL, Business Intelligence, Statistical Modelling, Predictive Analytics
Further Information:
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. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The next logical step from this position is a senior or lead-track role within the same function. Most days include at least one review checkpoint where progress is discussed against the plan for the week. 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. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Interested candidates should be prepared to walk through relevant past work during the interview process. Learning and certification support is available for tools and frameworks directly relevant to the role. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. The organisation has historically promoted from within for a majority of its senior and lead openings. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. 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. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Compensation includes standard statutory benefits along with performance-linked variable pay. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.