NLP Researcher – Language & Conversation

The IBM Language and Conversation research team is looking for  an enthusiastic AI researcher who majored in Deep Learning NLP to help us craft the future of IBM products and services, and push the boundaries on the state-of-the-art in language understanding, conversational systems and language generation.

Working as part of our team means you can bring your ideas to life through the full cycle of defining the research challenge, working with real data, performing the research, and innovating to solve and implement it. You will publish your research in top conferences, deliver it, and watch it come to life in the field.
If you love to create innovative algorithms, are passionate about applying technology to real-life problems, think out-of-the-box, and are interested in joining a group of top researchers solving challenging problems – your place is with us!

Job responsibilities

  • Conducting research in the area of language and conversation, advancing the state of the art, and publishing in top AI conferences
  • Initiating and leading new strategic research directions through a full lifecycle of inception, validation, experiments and implementation.
  • Efficiently implementing algorithms, defining data sets and benchmarks and running experiments on real data
  • Constantly reviewing relevant literature to identify emerging methods or technologies and current best practices
  • Following the market, products and understanding customer needs, to find innovative solutions to real customer problems.
  • Developing algorithms as software components and supporting their integration into IBM products

Why join us now?
Now is your chance to influence the next generation of conversational systems and language research.

Required Technical and Professional Expertise

  • PhD or MSc in computer science or related fields
  • Excellent academic record in the fields of Natural Language Processing and Deep Learning, Machine Learning, or Reinforcement Learning
  • Work experience in the above fields is an advantage
  • Deep and broad understanding of foundations up to state-of-the-art machine learning and deep learning techniques, including hands-on experience with deep learning frameworks. Experience in designing deep learning architectures, as well as implementing in a real-world setting.
  • Familiarity with NLP concepts and related tasks, such as language modeling, machine translation, summarization.
  • Hands on experience in writing code in Java and Python
  • Innovative thinking, creativity, and self-learning

Preferred Technical and Professional Experience

Extra points for

  • Excellent programming and engineering skills
  • Expertise in Knowledge Representation (semantic models, knowledge graphs, etc.) and reasoning

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