ML Engineer

You will be responsible for the following tasks: Data Collection and Curation. Selecting appropriate annotated datasets for Supervised Learning methods. Using effective text representations to transform natural language into useful features. Finding and implementing the right algorithms and tools for NLP tasks. Developing ML/DL/NLP models according to requirements. Training the developed model and running evaluation experiments. Performing statistical analysis of results and refining models. Extending ML libraries and frameworks to apply in NLP tasks. Building recommendation engines to increase the personalization of content for the user. Testing and deploying models on cloud services such as AWS/GCP. Acting as a bridge between product and engineering teams to translate product requirements into technical solutions. Staying updated on industry best practices and latest technology trends. Prototyping ideas rapidly using cutting edge technologies, driving architecture discussions, and proposing solutions to system and product changes. Having a deep understanding of NLP techniques for text representation, semantic extraction techniques, data structures, and language modeling. Experience with NLP libraries and technologies including Spacy, NLTK, Gensim, Stanford NLP, etc. Proficiency with Python and basic libraries for machine learning such as Numpy, Scikit-learn, and pandas. Exposure to DL Model optimization and transfer learning techniques. Experience of cloud environments like AWS/GCP, Hadoop/Spark, SQL is a plus. Experience with technologies like Docker, Kubernetes, CI/CD, Git is a plus. Experience with ML Ops is a plus. Please note that the company operates in the functional areas of data collection, curation, machine learning, ML Ops, Hadoop, Spark, Docker, Kubernetes, DL, NLP, AWS, GCP, and artificial intelligence. Apply now to be a part of the team. You will be responsible for the following tasks: Data Collection and Curation. Selecting appropriate annotated datasets for Supervised Learning methods. Using effective text representations to transform natural language into useful features. Finding and implementing the right algorithms and tools for NLP tasks. Developing ML/DL/NLP models according to requirements. Training the developed model and running evaluation experiments. Performing statistical analysis of results and refining models. Extending ML libraries and frameworks to apply in NLP tasks. Building recommendation engines to increase the personalization of content for the user. Testing and deploying models on cloud services such as AWS/GCP. Acting as a bridge between product and engineering teams to translate product requirements into technical solutions. Staying updated on industry best practices and latest technology trends. Prototyping ideas rapidly using cutting edge technologies, driving architecture discussions, and proposing solutions to system and product changes. Having a deep understanding of NLP techniques for text representation, semantic extraction techniques, data structures, and language modeling. Experience with NLP libraries and technologies including Spacy, NLTK, Gensim, Stanford NLP, etc. Proficiency with Python and basic libraries for machine learning such as Numpy, Scikit-learn, and pandas. Exposure to DL Model optimization and transfer learning techniques. Experience of cloud environments like AWS/GCP, Hadoop/Spark, SQL is a plus. Experience with technologies like Docker, Kubernetes, CI/CD, Git is a plus. Experience with ML Ops is a plus. Please note that the company operates in the functional areas of data collection, curation, machine learning, ML Ops, Hadoop, Spark, Docker, Kubernetes, DL, NLP, AWS, GCP, and artificial intelligence. Apply now to be a part of the team.