Job Description
We are looking to onboard an AI & Deep Learning Engineer – Generative Models to strengthen our Generative AI function within Artificial Intelligence (AI). This is a mid level opening based out of Chandigarh, offered on a full-time basis.
The ideal candidate holds M.Tech (AI/ML) and brings roughly 3 years of hands-on exposure to generative ai. Day-to-day, the work draws heavily on Statistical Modelling, Model Deployment (MLOps), Data Preprocessing, Machine Learning, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 19.2-36.8 LPA, in line with market standards for mid level roles within artificial intelligence (ai).
The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. 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 is a defined internal mobility path for people who want to specialise deeper or move into people management. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The next logical step from this position is a senior or lead-track role within the same function.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. High performers in this role typically move into a broader ownership scope within 18-24 months. 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. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
References may be requested closer to the offer stage rather than at the start of the process. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. The organisation has historically promoted from within for a majority of its senior and lead openings. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Compensation includes standard statutory benefits along with performance-linked variable pay. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
Learning and certification support is available for tools and frameworks directly relevant to the role. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
Interested candidates should be prepared to walk through relevant past work during the interview process. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
Internal job postings are open to employees who've completed a minimum tenure in their current role. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
This is a good fit for someone who wants real ownership rather than a purely execution-only role.
The ideal candidate holds M.Tech (AI/ML) and brings roughly 3 years of hands-on exposure to generative ai. Day-to-day, the work draws heavily on Statistical Modelling, Model Deployment (MLOps), Data Preprocessing, Machine Learning, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 19.2-36.8 LPA, in line with market standards for mid level roles within artificial intelligence (ai).
The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. 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 is a defined internal mobility path for people who want to specialise deeper or move into people management. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The next logical step from this position is a senior or lead-track role within the same function.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. High performers in this role typically move into a broader ownership scope within 18-24 months. 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. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
References may be requested closer to the offer stage rather than at the start of the process. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. The organisation has historically promoted from within for a majority of its senior and lead openings. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Compensation includes standard statutory benefits along with performance-linked variable pay. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
Learning and certification support is available for tools and frameworks directly relevant to the role. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
Interested candidates should be prepared to walk through relevant past work during the interview process. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
Internal job postings are open to employees who've completed a minimum tenure in their current role. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
This is a good fit for someone who wants real ownership rather than a purely execution-only role.