Job Description
Join us as a Machine Learning Deployment Engineer and help us push Machine Learning Engineering forward within Machine Learning.
You'll be working out of Chandigarh (full-time (wfh)), and honestly, the day-to-day is going to revolve around Machine Learning Engineering and Cloud Platforms (AWS/GCP). 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 B.Tech (CS/AI) and somewhere around 3 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 13.6-43.9 LPA - fair for the mid level band and open to discussion based on what you bring.
Learning and certification support is available for tools and frameworks directly relevant to the role. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
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.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. References may be requested closer to the offer stage rather than at the start of the process.
In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
Compensation includes standard statutory benefits along with performance-linked variable pay. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. 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.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Interested candidates should be prepared to walk through relevant past work during the interview process.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. The organisation has historically promoted from within for a majority of its senior and lead openings.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The next logical step from this position is a senior or lead-track role within the same function. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
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 package is structured with a fixed component, performance bonus, and standard health coverage. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. High performers in this role typically move into a broader ownership scope within 18-24 months. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
You'll be working out of Chandigarh (full-time (wfh)), and honestly, the day-to-day is going to revolve around Machine Learning Engineering and Cloud Platforms (AWS/GCP). 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 B.Tech (CS/AI) and somewhere around 3 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 13.6-43.9 LPA - fair for the mid level band and open to discussion based on what you bring.
Learning and certification support is available for tools and frameworks directly relevant to the role. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
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.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. References may be requested closer to the offer stage rather than at the start of the process.
In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
Compensation includes standard statutory benefits along with performance-linked variable pay. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. 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.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Interested candidates should be prepared to walk through relevant past work during the interview process.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. The organisation has historically promoted from within for a majority of its senior and lead openings.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The next logical step from this position is a senior or lead-track role within the same function. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
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 package is structured with a fixed component, performance bonus, and standard health coverage. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. High performers in this role typically move into a broader ownership scope within 18-24 months. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.