Description:

Position Required Skills, Knowledge, and Abilities: 5 years in designing high-level architectures and solutions for large-scale ML systems and/or building solutions for a product on AI / ML features/capabilities. Strong background in industry use cases built on deep learning and machine learning (unsupervised and supervised techniques) is a must. Deep learning frameworks such as TensorFlow, Keras, PyTorch Time series analysis, anomaly detection, forecasting, predictive modeling, graph-based neural networks, and Bayesian statistics are good to have. Deep learning architectures like RNN, CNN, LSTM, and Transformers Strong command of Python or equivalent language for ML Graph databases, analytics, and graph neural networks Data structures and ability to develop efficient solutions. Excellent verbal and written communication skills, especially the ability to share technical results and recommendations with both, technical and non-technical audience. Ability to perform high-level work both independently and collaboratively as a project member or leader on multiple projects. Position Education and Experience (required and preferred): B.E./ B.Tech. degree in Computer Science or equivalent from a reputed institute An advanced degree in predictive analytics, machine learning, or artificial intelligence; or a degree in programming and significant experience with text analytics / NLP Position Responsibilities: Showcase business acumen to translate requirements into ML problems. Lead ML teams and build, designed, and drive solutions to deliver. Guide teams in evaluating the quality of ML models and, review and define the right performance metrics for models in accordance with the requirements of the core platform. Be responsible for building new and innovative solutions leveraging data science and artificial intelligence skills/technologies to solve non-trivial problems. Lead teams of data scientists and ML engineers, reviewing the team s work and troubleshooting models implemented.

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