Job Description
Looking for a Generative AI Platform Architect who's genuinely interested in Generative AI and wants to make an impact from day one.
You'll be working out of Hyderabad (full-time), and honestly, the day-to-day is going to revolve around TensorFlow/PyTorch and Feature Engineering. 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 8 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 11.9-57.8 LPA - fair for the senior level band and open to discussion based on what you bring.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Compensation includes standard statutory benefits along with performance-linked variable pay. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
The package is structured with a fixed component, performance bonus, and standard health coverage. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Internal job postings are open to employees who've completed a minimum tenure in their current role. Learning and certification support is available for tools and frameworks directly relevant to the role. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
You'll be working out of Hyderabad (full-time), and honestly, the day-to-day is going to revolve around TensorFlow/PyTorch and Feature Engineering. 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 8 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 11.9-57.8 LPA - fair for the senior level band and open to discussion based on what you bring.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Compensation includes standard statutory benefits along with performance-linked variable pay. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
The package is structured with a fixed component, performance bonus, and standard health coverage. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Internal job postings are open to employees who've completed a minimum tenure in their current role. Learning and certification support is available for tools and frameworks directly relevant to the role. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.