Job Description
This position calls for a Reinforcement Learning Engineer who can take ownership of core responsibilities within our AI Research & Development team. This is a mid level opening based out of Lucknow, offered on a contract basis.
The ideal candidate holds M.Tech (AI/ML) and brings roughly 3 years of hands-on exposure to ai research & development. Day-to-day, the work draws heavily on Machine Learning, Python, AI Research, Development, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 26.9-41.5 LPA, in line with market standards for mid level roles within artificial intelligence (ai).
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Learning and certification support is available for tools and frameworks directly relevant to the role.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The next logical step from this position is a senior or lead-track role within the same function.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
Internal job postings are open to employees who've completed a minimum tenure in their current role. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
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.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
References may be requested closer to the offer stage rather than at the start of the process. High performers in this role typically move into a broader ownership scope within 18-24 months.
This role offers a genuine opportunity to build depth in AI Research & Development while working alongside an experienced team.
The ideal candidate holds M.Tech (AI/ML) and brings roughly 3 years of hands-on exposure to ai research & development. Day-to-day, the work draws heavily on Machine Learning, Python, AI Research, Development, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 26.9-41.5 LPA, in line with market standards for mid level roles within artificial intelligence (ai).
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Learning and certification support is available for tools and frameworks directly relevant to the role.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The next logical step from this position is a senior or lead-track role within the same function.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
Internal job postings are open to employees who've completed a minimum tenure in their current role. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
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.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
References may be requested closer to the offer stage rather than at the start of the process. High performers in this role typically move into a broader ownership scope within 18-24 months.
This role offers a genuine opportunity to build depth in AI Research & Development while working alongside an experienced team.