Job Description
**AI Algorithm Developer** | Hybrid - Pune | Full-time | INR 19.4-30.9 LPA
**About the role:**
- Position within AI Research & Development, under the Artificial Intelligence (AI) vertical
- Level: mid level
- Reports to the functional head for AI Research & Development
**What you'll do:**
- Handle core ai research & development activities on a day-to-day basis
- Use Neural Network Architectures 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:**
- Neural Network Architectures
- AI Research
- Data Preprocessing
- Development
- Statistical Modelling
- Model Deployment (MLOps)
- M.Tech (AI/ML)
- 3+ years of relevant experience
**Good to know:**
- The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
- Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. References may be requested closer to the offer stage rather than at the start of the process.
- No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
- Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Interested candidates should be prepared to walk through relevant past work during the interview process.
- 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. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
- The next logical step from this position is a senior or lead-track role within the same function. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
- Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
- Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The package is structured with a fixed component, performance bonus, and standard health coverage.
- The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
- Internal job postings are open to employees who've completed a minimum tenure in their current role. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
- Compensation includes standard statutory benefits along with performance-linked variable pay. The organisation has historically promoted from within for a majority of its senior and lead openings.
- There is a defined internal mobility path for people who want to specialise deeper or move into people management. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
**About the role:**
- Position within AI Research & Development, under the Artificial Intelligence (AI) vertical
- Level: mid level
- Reports to the functional head for AI Research & Development
**What you'll do:**
- Handle core ai research & development activities on a day-to-day basis
- Use Neural Network Architectures 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:**
- Neural Network Architectures
- AI Research
- Data Preprocessing
- Development
- Statistical Modelling
- Model Deployment (MLOps)
- M.Tech (AI/ML)
- 3+ years of relevant experience
**Good to know:**
- The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
- Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. References may be requested closer to the offer stage rather than at the start of the process.
- No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
- Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Interested candidates should be prepared to walk through relevant past work during the interview process.
- 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. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
- The next logical step from this position is a senior or lead-track role within the same function. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
- Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
- Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The package is structured with a fixed component, performance bonus, and standard health coverage.
- The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
- Internal job postings are open to employees who've completed a minimum tenure in their current role. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
- Compensation includes standard statutory benefits along with performance-linked variable pay. The organisation has historically promoted from within for a majority of its senior and lead openings.
- There is a defined internal mobility path for people who want to specialise deeper or move into people management. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.