Job Description
We're hiring a Computer Vision Systems Engineer to join our growing Computer Vision team - if this sounds like your kind of work, read on.
You'll be working out of Mumbai (full-time), and honestly, the day-to-day is going to revolve around Feature Engineering and Data Preprocessing. We're not looking for someone who just ticks boxes - we want someone who actually cares about computer vision.
On paper, we'd expect M.Tech (Machine Learning) and somewhere around 3 years of experience, but we're just as interested in how you think as in what's on your resume.
Pay-wise, we're offering INR 9.3-36.8 LPA - fair for the mid level band and open to discussion based on what you bring.
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.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
Internal job postings are open to employees who've completed a minimum tenure in their current role. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Relocation assistance may be extended for candidates moving from a different city, subject to approval. The package is structured with a fixed component, performance bonus, and standard health coverage.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Interested candidates should be prepared to walk through relevant past work during the interview process. 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.
You'll be working out of Mumbai (full-time), and honestly, the day-to-day is going to revolve around Feature Engineering and Data Preprocessing. We're not looking for someone who just ticks boxes - we want someone who actually cares about computer vision.
On paper, we'd expect M.Tech (Machine Learning) and somewhere around 3 years of experience, but we're just as interested in how you think as in what's on your resume.
Pay-wise, we're offering INR 9.3-36.8 LPA - fair for the mid level band and open to discussion based on what you bring.
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.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
Internal job postings are open to employees who've completed a minimum tenure in their current role. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Relocation assistance may be extended for candidates moving from a different city, subject to approval. The package is structured with a fixed component, performance bonus, and standard health coverage.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Interested candidates should be prepared to walk through relevant past work during the interview process. 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.