Job Description
Deep Learning Lab Associate | Gurugram | INR 8.3-14.0 LPA
Deep Learning role, junior level, full-time.
Need: B.Tech (CS/AI), 2+ yrs.
Core skills: Cloud Platforms (AWS/GCP), MLOps, Deep Learning, Python.
If this fits your profile in deep learning, apply now.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
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. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Compensation includes standard statutory benefits along with performance-linked variable pay. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
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.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. High performers in this role typically move into a broader ownership scope within 18-24 months. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
Learning and certification support is available for tools and frameworks directly relevant to the role. The organisation has historically promoted from within for a majority of its senior and lead openings. References may be requested closer to the offer stage rather than at the start of the process.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
Deep Learning role, junior level, full-time.
Need: B.Tech (CS/AI), 2+ yrs.
Core skills: Cloud Platforms (AWS/GCP), MLOps, Deep Learning, Python.
If this fits your profile in deep learning, apply now.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
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. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Compensation includes standard statutory benefits along with performance-linked variable pay. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
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.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. High performers in this role typically move into a broader ownership scope within 18-24 months. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
Learning and certification support is available for tools and frameworks directly relevant to the role. The organisation has historically promoted from within for a majority of its senior and lead openings. References may be requested closer to the offer stage rather than at the start of the process.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.