Job Description
Generative AI Optimization Engineer | Lucknow | INR 20.5-48.5 LPA
Generative AI role, mid level, hybrid.
Need: M.Tech (Machine Learning), 4+ yrs.
Core skills: Generative AI, Deep Learning, Machine Learning Algorithms, Cloud Platforms (AWS/GCP), Computer Vision/NLP Basics.
If this fits your profile in generative ai, apply now.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Learning and certification support is available for tools and frameworks directly relevant to the role.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. 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. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Internal job postings are open to employees who've completed a minimum tenure in their current role.
High performers in this role typically move into a broader ownership scope within 18-24 months. The organisation has historically promoted from within for a majority of its senior and lead openings. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
Compensation includes standard statutory benefits along with performance-linked variable pay. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
Generative AI role, mid level, hybrid.
Need: M.Tech (Machine Learning), 4+ yrs.
Core skills: Generative AI, Deep Learning, Machine Learning Algorithms, Cloud Platforms (AWS/GCP), Computer Vision/NLP Basics.
If this fits your profile in generative ai, apply now.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Learning and certification support is available for tools and frameworks directly relevant to the role.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. 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. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Internal job postings are open to employees who've completed a minimum tenure in their current role.
High performers in this role typically move into a broader ownership scope within 18-24 months. The organisation has historically promoted from within for a majority of its senior and lead openings. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
Compensation includes standard statutory benefits along with performance-linked variable pay. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.