Job Description
**Deep Learning Specialist** | Kochi | Full-time (WFH) | INR 8.2-25.8 LPA
**About the role:**
- Position within Deep Learning, under the Artificial Intelligence (AI) vertical
- Level: mid level
- Reports to the functional head for Deep Learning
**What you'll do:**
- Handle core deep learning activities on a day-to-day basis
- Use Natural Language Processing regularly as part of core deliverables
- Work closely with adjacent teams to align priorities
- Track progress against agreed timelines and escalate issues proactively
**What you'll need:**
- Natural Language Processing
- Machine Learning
- Computer Vision
- Neural Network Architectures
- Deep Learning
- Statistical Modelling
- Python
- B.Tech (CS/AI)
- 4+ years of relevant experience
**Good to know:**
- Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
- High performers in this role typically move into a broader ownership scope within 18-24 months. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
- No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
- 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.
- Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
- The package is structured with a fixed component, performance bonus, and standard health coverage. Relocation assistance may be extended for candidates moving from a different city, subject to approval. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
- Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
- Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
- Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
- The organisation has historically promoted from within for a majority of its senior and lead openings. 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 next logical step from this position is a senior or lead-track role within the same function. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
- Learning and certification support is available for tools and frameworks directly relevant to the role. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
- Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Compensation includes standard statutory benefits along with performance-linked variable pay. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
- Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. 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. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
**About the role:**
- Position within Deep Learning, under the Artificial Intelligence (AI) vertical
- Level: mid level
- Reports to the functional head for Deep Learning
**What you'll do:**
- Handle core deep learning activities on a day-to-day basis
- Use Natural Language Processing regularly as part of core deliverables
- Work closely with adjacent teams to align priorities
- Track progress against agreed timelines and escalate issues proactively
**What you'll need:**
- Natural Language Processing
- Machine Learning
- Computer Vision
- Neural Network Architectures
- Deep Learning
- Statistical Modelling
- Python
- B.Tech (CS/AI)
- 4+ years of relevant experience
**Good to know:**
- Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
- High performers in this role typically move into a broader ownership scope within 18-24 months. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
- No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
- 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.
- Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
- The package is structured with a fixed component, performance bonus, and standard health coverage. Relocation assistance may be extended for candidates moving from a different city, subject to approval. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
- Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
- Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
- Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
- The organisation has historically promoted from within for a majority of its senior and lead openings. 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 next logical step from this position is a senior or lead-track role within the same function. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
- Learning and certification support is available for tools and frameworks directly relevant to the role. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
- Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Compensation includes standard statutory benefits along with performance-linked variable pay. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
- Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. 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. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.