Job Description
Join us as an AI Risk Modeling Specialist and help us push AI-driven Risk Management forward within Artificial Intelligence (AI).
You'll be working out of Indore (full-time), and honestly, the day-to-day is going to revolve around Model Deployment (MLOps) and Computer Vision. We're not looking for someone who just ticks boxes - we want someone who actually cares about ai-driven risk management.
On paper, we'd expect B.Tech (CS/AI) 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 8.0-19.8 LPA - fair for the mid level band and open to discussion based on what you bring.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Interested candidates should be prepared to walk through relevant past work during the interview process.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
Learning and certification support is available for tools and frameworks directly relevant to the role. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
The organisation has historically promoted from within for a majority of its senior and lead openings. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. Compensation includes standard statutory benefits along with performance-linked variable pay. References may be requested closer to the offer stage rather than at the start of the process.
The package is structured with a fixed component, performance bonus, and standard health coverage. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. 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 Indore (full-time), and honestly, the day-to-day is going to revolve around Model Deployment (MLOps) and Computer Vision. We're not looking for someone who just ticks boxes - we want someone who actually cares about ai-driven risk management.
On paper, we'd expect B.Tech (CS/AI) 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 8.0-19.8 LPA - fair for the mid level band and open to discussion based on what you bring.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Interested candidates should be prepared to walk through relevant past work during the interview process.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
Learning and certification support is available for tools and frameworks directly relevant to the role. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
The organisation has historically promoted from within for a majority of its senior and lead openings. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. Compensation includes standard statutory benefits along with performance-linked variable pay. References may be requested closer to the offer stage rather than at the start of the process.
The package is structured with a fixed component, performance bonus, and standard health coverage. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. 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.