Job Description
Position: Autonomous Systems Research Scientist
Function: Artificial Intelligence & Machine Learning
Industry: Academic Research
Grade: mid level
Location: Indore
Employment Type: Contract
Compensation: INR 13.0-21.6 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with artificial intelligence & machine learning, in accordance with the standards and processes laid down by Academic Research.
Minimum Qualification: M.Phil
Minimum Experience: 7 years
Core Competencies Required: Artificial Intelligence, Qualitative Analysis, Citation Management (EndNote/Zotero), Research Ethics, Machine Learning
Further Information:
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. 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. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The organisation has historically promoted from within for a majority of its senior and lead openings. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. High performers in this role typically move into a broader ownership scope within 18-24 months. 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. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Internal job postings are open to employees who've completed a minimum tenure in their current role. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Most days include at least one review checkpoint where progress is discussed against the plan for the week. Interested candidates should be prepared to walk through relevant past work during the interview process. Relocation assistance may be extended for candidates moving from a different city, subject to approval. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. References may be requested closer to the offer stage rather than at the start of the process. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
Function: Artificial Intelligence & Machine Learning
Industry: Academic Research
Grade: mid level
Location: Indore
Employment Type: Contract
Compensation: INR 13.0-21.6 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with artificial intelligence & machine learning, in accordance with the standards and processes laid down by Academic Research.
Minimum Qualification: M.Phil
Minimum Experience: 7 years
Core Competencies Required: Artificial Intelligence, Qualitative Analysis, Citation Management (EndNote/Zotero), Research Ethics, Machine Learning
Further Information:
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. 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. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The organisation has historically promoted from within for a majority of its senior and lead openings. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. High performers in this role typically move into a broader ownership scope within 18-24 months. 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. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Internal job postings are open to employees who've completed a minimum tenure in their current role. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Most days include at least one review checkpoint where progress is discussed against the plan for the week. Interested candidates should be prepared to walk through relevant past work during the interview process. Relocation assistance may be extended for candidates moving from a different city, subject to approval. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. References may be requested closer to the offer stage rather than at the start of the process. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.