Job Description
Associate Machine Learning Officer | Hybrid - Pune | INR 4.7-15.4 LPA
Quantum Machine Learning role, junior level, contract.
Need: B.Tech (CS/Physics), 0+ yrs.
Core skills: Linear Algebra & Quantum Mechanics Fundamentals, Python Programming, Quantum Algorithms, Quantum Machine Learning.
If this fits your profile in quantum machine learning, apply now.
The organisation has historically promoted from within for a majority of its senior and lead openings. 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. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. 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. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
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.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Learning and certification support is available for tools and frameworks directly relevant to the role. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Compensation includes standard statutory benefits along with performance-linked variable pay.
Quantum Machine Learning role, junior level, contract.
Need: B.Tech (CS/Physics), 0+ yrs.
Core skills: Linear Algebra & Quantum Mechanics Fundamentals, Python Programming, Quantum Algorithms, Quantum Machine Learning.
If this fits your profile in quantum machine learning, apply now.
The organisation has historically promoted from within for a majority of its senior and lead openings. 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. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. 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. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
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.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Learning and certification support is available for tools and frameworks directly relevant to the role. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Compensation includes standard statutory benefits along with performance-linked variable pay.