Vartit is seeking a Machine Learning Engineer to innovate in query understanding, intent classification, information retrieval, dialog systems, and natural language generation. The role involves designing and implementing state-of-the-art systems, conducting literature surveys, and building scalable platforms to analyze data and train models, with a focus on NLP and multimodal applications.
About the role
About the Role
At Vartit, we are looking for Engineers who are interested in pushing the boundaries in query understanding, intent classification, information retrieval, dialog systems, natural language generation etc. along with methods for resource constrained textual systems. We are looking for candidates who are passionate and inquisitive about Machine Learning with their main work in NLP and/or multimodal applications.
Responsibilities
Design and implement baselines and state-of-art systems in key initiatives around intent and query understanding, text classification, information retrieval etc. on noisy data.
Carry out extensive literature surveys on the works done in the related problem spaces.
Build a scalable platform to analyze the data, train and evaluate the models efficiently.
Collaborate with other engineers in the team to understand the challenges in the real life data.
Requirements
Good understanding of fundamental ML & math concepts like bias-variance tradeoff, sampling techniques, evaluation metrics, optimizers, loss functions etc.
Understand recent trends in NLP around transformers, language models, text classification, generative approaches for NLP, prompting techniques, question answering etc.
Interest in reading and applying research works presented in various conferences to the problem at hand.
Have submitted and presented research papers in conferences and/or workshops.
Excellent implementation skills in Python and Machine Learning Frameworks such as Pytorch, Tensorflow, HuggingFace etc.
Have done ML / DL courses in the natural processing domain.
Programming experience in Python, shell scripting and deploying machine learning models.