Job Description
Machine Learning is looking for an experienced Computer Vision Technical Lead to take ownership of the Computer Vision charter at a senior 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 9 years of progressively senior experience, holding M.Tech (Machine Learning), with a demonstrated track record across Data Preprocessing, Python, Statistical Modelling, Computer Vision, MLOps. 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 Coimbatore on a full-time arrangement. Compensation is benchmarked at INR 32.5-61.6 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.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. The next logical step from this position is a senior or lead-track role within the same function.
Learning and certification support is available for tools and frameworks directly relevant to the role. 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. 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. References may be requested closer to the offer stage rather than at the start of the process.
Compensation includes standard statutory benefits along with performance-linked variable pay. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Internal job postings are open to employees who've completed a minimum tenure in their current role. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
High performers in this role typically move into a broader ownership scope within 18-24 months. The organisation has historically promoted from within for a majority of its senior and lead openings.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. 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.
The successful candidate will bring approximately 9 years of progressively senior experience, holding M.Tech (Machine Learning), with a demonstrated track record across Data Preprocessing, Python, Statistical Modelling, Computer Vision, MLOps. 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 Coimbatore on a full-time arrangement. Compensation is benchmarked at INR 32.5-61.6 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.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. The next logical step from this position is a senior or lead-track role within the same function.
Learning and certification support is available for tools and frameworks directly relevant to the role. 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. 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. References may be requested closer to the offer stage rather than at the start of the process.
Compensation includes standard statutory benefits along with performance-linked variable pay. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Internal job postings are open to employees who've completed a minimum tenure in their current role. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
High performers in this role typically move into a broader ownership scope within 18-24 months. The organisation has historically promoted from within for a majority of its senior and lead openings.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. 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.