ML Engineer-130226-036

The ML Engineer role focuses on developing and deploying classical ML and deep learning models for Vision, NLP, and Media problems. Candidates will be responsible for the entire ML lifecycle – from model design and training to evaluation, integration, and collaboration with domain experts. Specific areas of specialization include image classification, object detection, segmentation (Vision), text classification, NER, similarity (NLP), and audio/video feature extraction, media embeddings, and quality optimization (Media). The role involves working with real-world datasets, incorporating business logic, and potentially integrating models into APIs or services.

Design, train, and evaluate classical ML and deep learning models (classification, regression, ranking, clustering, anomaly detection). Apply ML techniques to Vision, NLP, or Media problems. Perform feature engineering using structured and unstructured data. Select appropriate algorithms based on data and business context. Evaluate models for accuracy, bias, robustness, and stability. Integrate ML models into production systems and agent workflows. Collaborate with domain SMEs to encode business logic into models.