Job Description
## Machine Learning Implementation Specialist
**Department:** Machine Learning Engineering | **Industry:** Machine Learning
**Location:** Mumbai | **Job Type:** Contract | **CTC:** INR 6.0-18.1 LPA
### Role Overview
An opening exists for a Machine Learning Implementation Specialist to join the Machine Learning vertical, focused on Machine Learning Engineering. The role is positioned at the mid level and reports into the broader Machine Learning Engineering charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to machine learning engineering.
- Apply working knowledge of Deep Learning and Model Evaluation & Tuning to daily execution.
- Coordinate with cross-functional stakeholders within Machine Learning.
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Sc (Data Science) or equivalent qualification.
- 6 years of relevant experience (mid level).
- Working proficiency in: Deep Learning, Model Evaluation & Tuning, Data Preprocessing, Feature Engineering, Machine Learning Engineering, Python.
### Additional Notes
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Compensation includes standard statutory benefits along with performance-linked variable pay. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Interested candidates should be prepared to walk through relevant past work during the interview process. The next logical step from this position is a senior or lead-track role within the same function. 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. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. The organisation has historically promoted from within for a majority of its senior and lead openings. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. 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. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Most days include at least one review checkpoint where progress is discussed against the plan for the week. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Learning and certification support is available for tools and frameworks directly relevant to the role. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
**Department:** Machine Learning Engineering | **Industry:** Machine Learning
**Location:** Mumbai | **Job Type:** Contract | **CTC:** INR 6.0-18.1 LPA
### Role Overview
An opening exists for a Machine Learning Implementation Specialist to join the Machine Learning vertical, focused on Machine Learning Engineering. The role is positioned at the mid level and reports into the broader Machine Learning Engineering charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to machine learning engineering.
- Apply working knowledge of Deep Learning and Model Evaluation & Tuning to daily execution.
- Coordinate with cross-functional stakeholders within Machine Learning.
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Sc (Data Science) or equivalent qualification.
- 6 years of relevant experience (mid level).
- Working proficiency in: Deep Learning, Model Evaluation & Tuning, Data Preprocessing, Feature Engineering, Machine Learning Engineering, Python.
### Additional Notes
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Compensation includes standard statutory benefits along with performance-linked variable pay. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Interested candidates should be prepared to walk through relevant past work during the interview process. The next logical step from this position is a senior or lead-track role within the same function. 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. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. The organisation has historically promoted from within for a majority of its senior and lead openings. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. 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. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Most days include at least one review checkpoint where progress is discussed against the plan for the week. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Learning and certification support is available for tools and frameworks directly relevant to the role. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.