Job Description
Position: AI Model Development Engineer
Function: Machine Learning Engineering
Industry: Machine Learning
Grade: mid level
Location: Bengaluru
Employment Type: Full-time
Compensation: INR 7.1-19.4 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: M.Tech (Machine Learning)
Minimum Experience: 5 years
Core Competencies Required: Python, Cloud Platforms (AWS/GCP), Machine Learning Engineering, TensorFlow/PyTorch, Feature Engineering, Computer Vision/NLP Basics, Model Evaluation & Tuning
Further Information:
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Relocation assistance may be extended for candidates moving from a different city, subject to approval. Most days include at least one review checkpoint where progress is discussed against the plan for the week. There is a defined internal mobility path for people who want to specialise deeper or move into people management. References may be requested closer to the offer stage rather than at the start of the process. Internal job postings are open to employees who've completed a minimum tenure in their current role. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Interested candidates should be prepared to walk through relevant past work during the interview process. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The next logical step from this position is a senior or lead-track role within the same function. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
Function: Machine Learning Engineering
Industry: Machine Learning
Grade: mid level
Location: Bengaluru
Employment Type: Full-time
Compensation: INR 7.1-19.4 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: M.Tech (Machine Learning)
Minimum Experience: 5 years
Core Competencies Required: Python, Cloud Platforms (AWS/GCP), Machine Learning Engineering, TensorFlow/PyTorch, Feature Engineering, Computer Vision/NLP Basics, Model Evaluation & Tuning
Further Information:
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Relocation assistance may be extended for candidates moving from a different city, subject to approval. Most days include at least one review checkpoint where progress is discussed against the plan for the week. There is a defined internal mobility path for people who want to specialise deeper or move into people management. References may be requested closer to the offer stage rather than at the start of the process. Internal job postings are open to employees who've completed a minimum tenure in their current role. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Interested candidates should be prepared to walk through relevant past work during the interview process. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The next logical step from this position is a senior or lead-track role within the same function. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.