Job Description
Here's the deal: we need a Machine Learning Technical Lead who can hit the ground running on Machine Learning Engineering work.
You'll be working out of Delhi NCR (hybrid), and honestly, the day-to-day is going to revolve around Computer Vision/NLP Basics and Data Preprocessing. We're not looking for someone who just ticks boxes - we want someone who actually cares about machine learning engineering.
On paper, we'd expect M.Tech (Machine Learning) and somewhere around 16 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 54.0-104.1 LPA - fair for the senior level band and open to discussion based on what you bring.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
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.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. 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.
High performers in this role typically move into a broader ownership scope within 18-24 months. Compensation includes standard statutory benefits along with performance-linked variable pay. 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. The organisation has historically promoted from within for a majority of its senior and lead openings. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
Interested candidates should be prepared to walk through relevant past work during the interview process. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
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. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
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.
You'll be working out of Delhi NCR (hybrid), and honestly, the day-to-day is going to revolve around Computer Vision/NLP Basics and Data Preprocessing. We're not looking for someone who just ticks boxes - we want someone who actually cares about machine learning engineering.
On paper, we'd expect M.Tech (Machine Learning) and somewhere around 16 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 54.0-104.1 LPA - fair for the senior level band and open to discussion based on what you bring.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
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.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. 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.
High performers in this role typically move into a broader ownership scope within 18-24 months. Compensation includes standard statutory benefits along with performance-linked variable pay. 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. The organisation has historically promoted from within for a majority of its senior and lead openings. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
Interested candidates should be prepared to walk through relevant past work during the interview process. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
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. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
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.