Job Description
**Q: What experience is required?**
A: Around 14 years, consistent with a senior level profile.
**Q: What is this role about?**
A: We're hiring a Neural Network Architect to work within Deep Learning, part of the Machine Learning function.
**Q: What qualification is expected?**
A: M.Sc (Data Science) or an equivalent, relevant qualification.
**Q: What does compensation look like?**
A: INR 49.6-80.4 LPA, depending on experience and interview performance.
**Q: Where is this based?**
A: Ahmedabad, on a full-time basis.
**Q: What skills matter most?**
A: Feature Engineering, Cloud Platforms (AWS/GCP), Python, Deep Learning, Machine Learning Algorithms, Statistical Modelling, Model Evaluation & Tuning, TensorFlow/PyTorch.
**Q: What does a typical day look like?**
A: A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
**Q: What's the interview process like?**
A: Interested candidates should be prepared to walk through relevant past work during the interview process.
**Q: What's the team like?**
A: Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
**Q: Is there room to grow?**
A: Learning and certification support is available for tools and frameworks directly relevant to the role.
A: Around 14 years, consistent with a senior level profile.
**Q: What is this role about?**
A: We're hiring a Neural Network Architect to work within Deep Learning, part of the Machine Learning function.
**Q: What qualification is expected?**
A: M.Sc (Data Science) or an equivalent, relevant qualification.
**Q: What does compensation look like?**
A: INR 49.6-80.4 LPA, depending on experience and interview performance.
**Q: Where is this based?**
A: Ahmedabad, on a full-time basis.
**Q: What skills matter most?**
A: Feature Engineering, Cloud Platforms (AWS/GCP), Python, Deep Learning, Machine Learning Algorithms, Statistical Modelling, Model Evaluation & Tuning, TensorFlow/PyTorch.
**Q: What does a typical day look like?**
A: A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
**Q: What's the interview process like?**
A: Interested candidates should be prepared to walk through relevant past work during the interview process.
**Q: What's the team like?**
A: Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
**Q: Is there room to grow?**
A: Learning and certification support is available for tools and frameworks directly relevant to the role.