Job Description
The organisation is seeking a qualified AI Vision Systems Engineer to support ongoing initiatives in Computer Vision. This is a mid level opening based out of Lucknow, offered on a full-time basis.
The ideal candidate holds M.Tech (AI/ML) and brings roughly 3 years of hands-on exposure to computer vision. Day-to-day, the work draws heavily on Neural Network Architectures, Cloud Platforms (AWS/GCP/Azure), Machine Learning, Model Deployment (MLOps), and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 25.3-54.8 LPA, in line with market standards for mid level roles within artificial intelligence (ai).
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
The next logical step from this position is a senior or lead-track role within the same function. 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.
References may be requested closer to the offer stage rather than at the start of the process. Learning and certification support is available for tools and frameworks directly relevant to the role. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
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. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
High performers in this role typically move into a broader ownership scope within 18-24 months. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. Interested candidates should be prepared to walk through relevant past work during the interview process.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. 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. 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.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. 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's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. 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. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
This role offers a genuine opportunity to build depth in Computer Vision while working alongside an experienced team.
The ideal candidate holds M.Tech (AI/ML) and brings roughly 3 years of hands-on exposure to computer vision. Day-to-day, the work draws heavily on Neural Network Architectures, Cloud Platforms (AWS/GCP/Azure), Machine Learning, Model Deployment (MLOps), and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 25.3-54.8 LPA, in line with market standards for mid level roles within artificial intelligence (ai).
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
The next logical step from this position is a senior or lead-track role within the same function. 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.
References may be requested closer to the offer stage rather than at the start of the process. Learning and certification support is available for tools and frameworks directly relevant to the role. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
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. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
High performers in this role typically move into a broader ownership scope within 18-24 months. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. Interested candidates should be prepared to walk through relevant past work during the interview process.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. 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. 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.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. 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's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. 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. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
This role offers a genuine opportunity to build depth in Computer Vision while working alongside an experienced team.