Working with the data science team in building/optimizing the current DL systems.
Own the model building and model deployment tasks like data collection, data cleaning, creating data pipelines, generating & analyzing model output, model validations, and deploying them in production.
Sync/rotate between internal product work and client deployment work.
Work closely with product managers and management team on micro, and macro goals.
Participate in the product discussions and contribute to the product development roadmap.
Work firsthand with customer teams on data understanding, use case building, requirements, and feasibility analysis.
Requirements:
Strong academic background in concepts of machine learning and deep learning.
Hands-on experience in working with deep learning frameworks like TensorFlow, PyTorch, etc.
Enjoys working on various DL problems that involve using different types of training data sets - textual, tabular, categorical, images, etc.
Comfortable deploying code in cloud environments/on-premise environments.
Should be comfortable and flexible in working in an environment where priorities evolve.
Writes clean code has the habit of maintaining a clean documented code
Understands best practices in ML/DL and is continuously open to learning.