Job Description
Machine Learning is looking for an experienced AI Vision Systems Engineer to take ownership of the Computer Vision charter at a mid level. This is a role for someone who has already operated at scale and is comfortable setting direction rather than simply following one.
The successful candidate will bring approximately 6 years of progressively senior experience, holding M.Tech (Machine Learning), with a demonstrated track record across Deep Learning, Model Evaluation & Tuning, Python, Computer Vision, Computer Vision/NLP Basics. Beyond individual capability, this role expects the person to mentor junior team members and represent the function in cross-departmental discussions.
Reporting relationships will be defined based on the final scope agreed at offer stage, and the role is based out of Nagpur on a full-time arrangement. Compensation is benchmarked at INR 25.3-56.6 LPA, reflecting the seniority and scope of the position.
Success in this role will be measured less by task completion and more by the quality of judgement applied to ambiguous, high-stakes situations within computer vision.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
The organisation has historically promoted from within for a majority of its senior and lead openings. Learning and certification support is available for tools and frameworks directly relevant to the role. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
References may be requested closer to the offer stage rather than at the start of the process. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. 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. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The package is structured with a fixed component, performance bonus, and standard health coverage. 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. Interested candidates should be prepared to walk through relevant past work during the interview process.
The next logical step from this position is a senior or lead-track role within the same function. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
The successful candidate will bring approximately 6 years of progressively senior experience, holding M.Tech (Machine Learning), with a demonstrated track record across Deep Learning, Model Evaluation & Tuning, Python, Computer Vision, Computer Vision/NLP Basics. Beyond individual capability, this role expects the person to mentor junior team members and represent the function in cross-departmental discussions.
Reporting relationships will be defined based on the final scope agreed at offer stage, and the role is based out of Nagpur on a full-time arrangement. Compensation is benchmarked at INR 25.3-56.6 LPA, reflecting the seniority and scope of the position.
Success in this role will be measured less by task completion and more by the quality of judgement applied to ambiguous, high-stakes situations within computer vision.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
The organisation has historically promoted from within for a majority of its senior and lead openings. Learning and certification support is available for tools and frameworks directly relevant to the role. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
References may be requested closer to the offer stage rather than at the start of the process. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. 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. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The package is structured with a fixed component, performance bonus, and standard health coverage. 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. Interested candidates should be prepared to walk through relevant past work during the interview process.
The next logical step from this position is a senior or lead-track role within the same function. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.