Job Description
**Robotics Architect** | Coimbatore | Hybrid | INR 14.3-56.2 LPA
**About the role:**
- Position within Robotics and Autonomous Systems, under the Machine Learning vertical
- Level: senior level
- Reports to the functional head for Robotics and Autonomous Systems
**What you'll do:**
- Handle core robotics and autonomous systems activities on a day-to-day basis
- Use Machine Learning Algorithms 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:**
- Machine Learning Algorithms
- Statistical Modelling
- Deep Learning
- Python
- MLOps
- Robotics and Autonomous Systems
- Feature Engineering
- Model Evaluation & Tuning
- Computer Vision/NLP Basics
- M.Sc (Data Science)
- 9+ years of relevant experience
**Good to know:**
- Relocation assistance may be extended for candidates moving from a different city, subject to approval. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
- Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. High performers in this role typically move into a broader ownership scope within 18-24 months.
- A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
- 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. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
- Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Internal job postings are open to employees who've completed a minimum tenure in their current role.
- Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Interested candidates should be prepared to walk through relevant past work during the interview process.
- The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Learning and certification support is available for tools and frameworks directly relevant to the role.
- New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. 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. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
- The organisation has historically promoted from within for a majority of its senior and lead openings. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
- Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
- The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
- Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
**About the role:**
- Position within Robotics and Autonomous Systems, under the Machine Learning vertical
- Level: senior level
- Reports to the functional head for Robotics and Autonomous Systems
**What you'll do:**
- Handle core robotics and autonomous systems activities on a day-to-day basis
- Use Machine Learning Algorithms 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:**
- Machine Learning Algorithms
- Statistical Modelling
- Deep Learning
- Python
- MLOps
- Robotics and Autonomous Systems
- Feature Engineering
- Model Evaluation & Tuning
- Computer Vision/NLP Basics
- M.Sc (Data Science)
- 9+ years of relevant experience
**Good to know:**
- Relocation assistance may be extended for candidates moving from a different city, subject to approval. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
- Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. High performers in this role typically move into a broader ownership scope within 18-24 months.
- A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
- 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. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
- Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Internal job postings are open to employees who've completed a minimum tenure in their current role.
- Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Interested candidates should be prepared to walk through relevant past work during the interview process.
- The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Learning and certification support is available for tools and frameworks directly relevant to the role.
- New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. 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. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
- The organisation has historically promoted from within for a majority of its senior and lead openings. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
- Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
- The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
- Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.