Job Description
Here's the deal: we need an AI Transformation Research Assistant who can hit the ground running on AI Strategy & Business Integration work.
You'll be working out of Bhubaneswar (full-time), and honestly, the day-to-day is going to revolve around Model Evaluation & Tuning and Machine Learning Algorithms. We're not looking for someone who just ticks boxes - we want someone who actually cares about ai strategy & business integration.
On paper, we'd expect M.Tech (Machine Learning) and somewhere around 1 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 12.1-21.6 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. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
The next logical step from this position is a senior or lead-track role within the same function. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. The package is structured with a fixed component, performance bonus, and standard health coverage.
Learning and certification support is available for tools and frameworks directly relevant to the role. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
You'll be working out of Bhubaneswar (full-time), and honestly, the day-to-day is going to revolve around Model Evaluation & Tuning and Machine Learning Algorithms. We're not looking for someone who just ticks boxes - we want someone who actually cares about ai strategy & business integration.
On paper, we'd expect M.Tech (Machine Learning) and somewhere around 1 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 12.1-21.6 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. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
The next logical step from this position is a senior or lead-track role within the same function. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. The package is structured with a fixed component, performance bonus, and standard health coverage.
Learning and certification support is available for tools and frameworks directly relevant to the role. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.