Job Description
Position: Generative AI Systems Engineer
Function: Generative AI
Industry: Machine Learning
Grade: mid level
Location: Remote (Pan India)
Employment Type: Full-time
Compensation: INR 13.7-33.1 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with generative ai, in accordance with the standards and processes laid down by Machine Learning.
Minimum Qualification: M.Tech (Machine Learning)
Minimum Experience: 7 years
Core Competencies Required: Deep Learning, Generative AI, Model Evaluation & Tuning, Statistical Modelling, Python
Further Information:
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. The package is structured with a fixed component, performance bonus, and standard health coverage. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. The organisation has historically promoted from within for a majority of its senior and lead openings. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Most days include at least one review checkpoint where progress is discussed against the plan for the week. 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. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Learning and certification support is available for tools and frameworks directly relevant to the role. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. 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. Interested candidates should be prepared to walk through relevant past work during the interview process. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. High performers in this role typically move into a broader ownership scope within 18-24 months. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Function: Generative AI
Industry: Machine Learning
Grade: mid level
Location: Remote (Pan India)
Employment Type: Full-time
Compensation: INR 13.7-33.1 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with generative ai, in accordance with the standards and processes laid down by Machine Learning.
Minimum Qualification: M.Tech (Machine Learning)
Minimum Experience: 7 years
Core Competencies Required: Deep Learning, Generative AI, Model Evaluation & Tuning, Statistical Modelling, Python
Further Information:
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. The package is structured with a fixed component, performance bonus, and standard health coverage. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. The organisation has historically promoted from within for a majority of its senior and lead openings. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Most days include at least one review checkpoint where progress is discussed against the plan for the week. 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. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Learning and certification support is available for tools and frameworks directly relevant to the role. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. 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. Interested candidates should be prepared to walk through relevant past work during the interview process. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. High performers in this role typically move into a broader ownership scope within 18-24 months. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.