Artificial Intelligence & Machine Learning

PhD Research Scholar – AI & ML

  • Coimbatore
  • ₹320,000 - ₹850,000
  • Freelancing Job

Job Description

Academic Research is looking for an experienced PhD Research Scholar – 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 1 years of progressively senior experience, holding B.Sc, with a demonstrated track record across Quantitative Analysis, Machine Learning, Artificial Intelligence, Peer Review, Presentation Skills. 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 3.2-8.5 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.

In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.

Learning and certification support is available for tools and frameworks directly relevant to the role. 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.

Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.

Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.

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