Job Description
Machine Learning is looking for an experienced Enterprise Robotics Architect to take ownership of the Robotics and Autonomous Systems charter at a senior level. This is a role for someone who has already operated at scale and is comfortable setting direction rather than simply following one.
The successful candidate will bring approximately 10 years of progressively senior experience, holding Ph.D (ML/AI), with a demonstrated track record across Data Preprocessing, Machine Learning Algorithms, Python, Robotics and Autonomous Systems, Statistical Modelling. Beyond individual capability, this role expects the person to mentor junior team members and represent the function in cross-departmental discussions.
Reporting relationships will be defined based on the final scope agreed at offer stage, and the role is based out of Bengaluru on a full-time arrangement. Compensation is benchmarked at INR 48.5-111.1 LPA, reflecting the seniority and scope of the position.
Success in this role will be measured less by task completion and more by the quality of judgement applied to ambiguous, high-stakes situations within robotics and autonomous systems.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
High performers in this role typically move into a broader ownership scope within 18-24 months. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
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.
Learning and certification support is available for tools and frameworks directly relevant to the role. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
The successful candidate will bring approximately 10 years of progressively senior experience, holding Ph.D (ML/AI), with a demonstrated track record across Data Preprocessing, Machine Learning Algorithms, Python, Robotics and Autonomous Systems, Statistical Modelling. Beyond individual capability, this role expects the person to mentor junior team members and represent the function in cross-departmental discussions.
Reporting relationships will be defined based on the final scope agreed at offer stage, and the role is based out of Bengaluru on a full-time arrangement. Compensation is benchmarked at INR 48.5-111.1 LPA, reflecting the seniority and scope of the position.
Success in this role will be measured less by task completion and more by the quality of judgement applied to ambiguous, high-stakes situations within robotics and autonomous systems.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
High performers in this role typically move into a broader ownership scope within 18-24 months. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
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.
Learning and certification support is available for tools and frameworks directly relevant to the role. Most days include at least one review checkpoint where progress is discussed against the plan for the week.