Job Description
## Senior AI Neural Engineer
**Department:** Deep Learning | **Industry:** Machine Learning
**Location:** Bengaluru | **Job Type:** Full-time | **CTC:** INR 36.6-58.2 LPA
### Role Overview
This position calls for a Senior AI Neural Engineer who can take ownership of core responsibilities within our Deep Learning team. The role is positioned at the senior level and reports into the broader Deep Learning charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to deep learning.
- Apply working knowledge of Model Evaluation & Tuning and Deep Learning to daily execution.
- Coordinate with cross-functional stakeholders within Machine Learning.
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Sc (Data Science) or equivalent qualification.
- 8 years of relevant experience (senior level).
- Working proficiency in: Model Evaluation & Tuning, Deep Learning, Statistical Modelling, Machine Learning Algorithms, Feature Engineering, TensorFlow/PyTorch, Python, Data Preprocessing, Cloud Platforms (AWS/GCP).
### Additional Notes
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Interested candidates should be prepared to walk through relevant past work during the interview process. 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. Relocation assistance may be extended for candidates moving from a different city, subject to approval. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. 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. The next logical step from this position is a senior or lead-track role within the same function. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Compensation includes standard statutory benefits along with performance-linked variable pay. Most days include at least one review checkpoint where progress is discussed against the plan for the week. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
**Department:** Deep Learning | **Industry:** Machine Learning
**Location:** Bengaluru | **Job Type:** Full-time | **CTC:** INR 36.6-58.2 LPA
### Role Overview
This position calls for a Senior AI Neural Engineer who can take ownership of core responsibilities within our Deep Learning team. The role is positioned at the senior level and reports into the broader Deep Learning charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to deep learning.
- Apply working knowledge of Model Evaluation & Tuning and Deep Learning to daily execution.
- Coordinate with cross-functional stakeholders within Machine Learning.
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Sc (Data Science) or equivalent qualification.
- 8 years of relevant experience (senior level).
- Working proficiency in: Model Evaluation & Tuning, Deep Learning, Statistical Modelling, Machine Learning Algorithms, Feature Engineering, TensorFlow/PyTorch, Python, Data Preprocessing, Cloud Platforms (AWS/GCP).
### Additional Notes
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Interested candidates should be prepared to walk through relevant past work during the interview process. 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. Relocation assistance may be extended for candidates moving from a different city, subject to approval. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. 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. The next logical step from this position is a senior or lead-track role within the same function. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Compensation includes standard statutory benefits along with performance-linked variable pay. Most days include at least one review checkpoint where progress is discussed against the plan for the week. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.