Job Description
Position: AI Systems Developer (Junior)
Function: Machine Learning Engineering
Industry: Machine Learning
Grade: junior level
Location: Hyderabad
Employment Type: Full-time
Compensation: INR 8.7-19.8 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with machine learning engineering, in accordance with the standards and processes laid down by Machine Learning.
Minimum Qualification: B.Tech (CS/AI)
Minimum Experience: 2 years
Core Competencies Required: Machine Learning Algorithms, Machine Learning Engineering, MLOps, Python
Further Information:
Most days include at least one review checkpoint where progress is discussed against the plan for the week. High performers in this role typically move into a broader ownership scope within 18-24 months. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. 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. Learning and certification support is available for tools and frameworks directly relevant to the role. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. 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 package is structured with a fixed component, performance bonus, and standard health coverage. The next logical step from this position is a senior or lead-track role within the same function. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Function: Machine Learning Engineering
Industry: Machine Learning
Grade: junior level
Location: Hyderabad
Employment Type: Full-time
Compensation: INR 8.7-19.8 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with machine learning engineering, in accordance with the standards and processes laid down by Machine Learning.
Minimum Qualification: B.Tech (CS/AI)
Minimum Experience: 2 years
Core Competencies Required: Machine Learning Algorithms, Machine Learning Engineering, MLOps, Python
Further Information:
Most days include at least one review checkpoint where progress is discussed against the plan for the week. High performers in this role typically move into a broader ownership scope within 18-24 months. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. 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. Learning and certification support is available for tools and frameworks directly relevant to the role. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. 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 package is structured with a fixed component, performance bonus, and standard health coverage. The next logical step from this position is a senior or lead-track role within the same function. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.