Job Description
Here's the deal: we need an AI Prompt Engineering Assistant who can hit the ground running on Generative AI work.
You'll be working out of Kochi (internship), and honestly, the day-to-day is going to revolve around Feature Engineering and Deep Learning. We're not looking for someone who just ticks boxes - we want someone who actually cares about generative ai.
On paper, we'd expect M.Tech (Machine Learning) and somewhere around 0 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 10.0-21.2 LPA - fair for the junior level band and open to discussion based on what you bring.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Interested candidates should be prepared to walk through relevant past work during the interview process.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. Compensation includes standard statutory benefits along with performance-linked variable pay. Internal job postings are open to employees who've completed a minimum tenure in their current role.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. 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.
The package is structured with a fixed component, performance bonus, and standard health coverage. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
The organisation has historically promoted from within for a majority of its senior and lead openings. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
You'll be working out of Kochi (internship), and honestly, the day-to-day is going to revolve around Feature Engineering and Deep Learning. We're not looking for someone who just ticks boxes - we want someone who actually cares about generative ai.
On paper, we'd expect M.Tech (Machine Learning) and somewhere around 0 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 10.0-21.2 LPA - fair for the junior level band and open to discussion based on what you bring.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Interested candidates should be prepared to walk through relevant past work during the interview process.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. Compensation includes standard statutory benefits along with performance-linked variable pay. Internal job postings are open to employees who've completed a minimum tenure in their current role.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. 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.
The package is structured with a fixed component, performance bonus, and standard health coverage. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
The organisation has historically promoted from within for a majority of its senior and lead openings. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.