About the Role
Focuses on creating advanced machine learning models and AI-driven applications to solve complex business challenges. This
position ensures the development of robust, scalable, and efficient systems for real-world deployment. The engineer will collaborate
across teams to integrate AI solutions into production environments seamlessly.
1) Model & Solution Engineering
Key Responsibilities
- Translate business problems into ML formulations; select suitable architectures (e.g., gradient boosting, transformers) with clear success metrics.
- Build end-to-end pipelines: feature extraction, training, hyperparameter tuning, and packaging models as reproducible artifacts.
- Optimize inference (quantization, distillation, mixed precision) for latency and throughput on CPU/GPU.
- Conduct evaluation beyond accuracy (calibration, fairness, cost-sensitive metrics, PR/ROC under imbalance).
How to Apply
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