Job Description
Academic Research is looking for an experienced Graduate Research Assistant – AI & ML to take ownership of the Artificial Intelligence & Machine Learning charter at a junior 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 2 years of progressively senior experience, holding M.Sc, with a demonstrated track record across Peer Review, Artificial Intelligence, Machine Learning, Experimental Design, Statistical Software (SPSS/R). 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 Coimbatore on a full-time arrangement. Compensation is benchmarked at INR 4.8-13.3 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 artificial intelligence & machine learning.
References may be requested closer to the offer stage rather than at the start of the process. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
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. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Learning and certification support is available for tools and frameworks directly relevant to the role.
The next logical step from this position is a senior or lead-track role within the same function. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
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. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
The successful candidate will bring approximately 2 years of progressively senior experience, holding M.Sc, with a demonstrated track record across Peer Review, Artificial Intelligence, Machine Learning, Experimental Design, Statistical Software (SPSS/R). 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 Coimbatore on a full-time arrangement. Compensation is benchmarked at INR 4.8-13.3 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 artificial intelligence & machine learning.
References may be requested closer to the offer stage rather than at the start of the process. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
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. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Learning and certification support is available for tools and frameworks directly relevant to the role.
The next logical step from this position is a senior or lead-track role within the same function. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
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. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.