Responsibilities Develop ML or DL models for application areas such as NLP, Computer Vision, and Analytics Experiment with various algorithms, design, code, train/test, deploy and benchmark the models and create enterprise-scale ML solutions Design and implement production-quality software in a cloud-based environment Troubleshoot and provide timely resolutions to product development and support issues Write high-quality code and provide feedback relative to best practices and improving performance Have quality assurance in mind and implement software with a high level of test coverage Analyze product requirements for completeness and potential impacts Take ownership of features from beginning to end - from design and reviews to deployment Being up to date with the latest trends and sharing insights with the internal team Participate in brainstorming sessions and be a creative influence in the product development process Should be self-sufficient and proactive in their work and implement best-practice processes Continually improve your own skills and knowledge
Requirements Solid understanding of algorithms, data structures, data modeling and software architecture Solid programming skills in python and basic know-how in C#/java Experience in ML, DL (Tensorflow/ Keras/PyTorch), NLP, and NLU (NLTK, Spacy, Flair, etc.) Good understanding and relevant experience in ML techniques/ NLP/ Computer Vision tasks such as classification, clustering, deep learning, optimization methods, NER, dependency parsing, boundary detection, etc. Fluency in Python: Pandas, NumPy, SciPy, PyTorch, Matplotlib Techniques: Regression analysis, Natural Language Processing (NLP) models, CNN DNN, Decision tree, Deep learning algorithms. Experience any of the database technology such as MySQL, Postgres, Oracle, and NoSQL databases Working experience with GCP, AWS, and other cloud-based ML services is a plus Knowledge of AWS Sagemaker will be a plus Experience working with remote engineering teams