Lead the development of transformer-based deep learning models and algorithms to solve complex business challenges by exploring various approaches to enhance accuracy and efficiency
Manage large datasets for preprocessing and feature engineering, partnering with data engineering teams to ensure data quality and accessibility
Drive the training and evaluation of machine learning models, employing suitable frameworks and libraries to accomplish target performance metrics
Collaborate closely with software engineering teams to deploy models into production, ensuring seamless integration with current systems
Commit to the ongoing improvement of machine learning models and methodologies, keeping pace with industry advancements and fostering a culture of knowledge exchange within the team
Job Requirements:
Bachelor s/Master s degree in Engineering, Computer Science (or equivalent experience)
A minimum of 5 years of experience in a Machine Learning role, emphasizing hands-on transformer-based deep learning model development and deployment
Strong proficiency in using Python for data science and familiarity with machine learning libraries such as TensorFlow and PyTorch
Expert-level knowledge in Natural Language Processing (NLP) and associated technologies, with a solid understanding of transformers applications
Demonstrated experience in data preprocessing, feature engineering, model training, evaluation, and deployment
A background in leveraging PyTorch, TensorFlow, or PySpark for complex data science projects
Experience in working with Deep Learning and an interest in other nice-to-have skills such as PyTorch and PySpark
Ability to dissect business problems and devise effective technical solutions, coupled with superior problem-solving skills
Excellent communication capabilities to work effectively across multidisciplinary teams and articulate technical concepts to non-technical stakeholders
Excellent spoken and written English communication