Collaborate with dozens of data scientists, machine learning scientists and deep learning specialists—PhD's and Masters grads with experience in deep learning, machine learning, big data, statistics, natural language processing, probabilistic programming and data visualization—at Thomson Reuters Labs around the world to build AI systems that push the boundaries of what was previously considered possible.
Continually research and learn how to apply state-of-the-art deep learning NLP techniques to keep your skills on the cutting edge of what is possible.
Interact with customers and internal business partners to understand their business challenges and develop hypotheses about AI solutions to real world problems in legal, regulatory, news and tax domains.
Run experiments with the latest deep learning models using frameworks such as TensorFlow and PyTorch, and toolkits such as Tensor2Tensor, Sockeye, and OpenNMT.
Develop new deep learning models and innovative machine learning pipelines to solve real world business problems.
Work with engineering teams to move your solutions into production.
2+ years of relevant experience in building machine learning models and/or systems
Ability to translate the latest technical papers into implementations addressing our use cases.
Development skills to rapidly deliver minimum viable products.
Strong experience with scripting languages like Python or R.
PhD or Masters in a data-heavy technical field, such as Computer Science, Engineering, Statistics, Mathematics, or other data-heavy discipline such as Physics or Chemistry or quantitative social science.
1+ years of experience specifically with one or more of:
Deep Learning (e.g. CNN, RNN, LSTM, Transformers, etc.)