Offers “IBM”

Expires soon IBM

AI Engineer

  • São Paulo, BRAZIL
  • IT development

Job description

IBM Research Scientists are charting the future of Artificial Intelligence, creating breakthroughs in quantum computing, discovering how blockchain will reshape the enterprise, and much more. Join a team that is dedicated to applying science to some of today's most complex challenges, whether it’s discovering a new way for doctors to help patients, teaming with environmentalists to clean up our waterways or enabling retailers to personalize customer service.

Your Role and Responsibilities

As an AI Engineer at IBM Research, you will play a pivotal role in driving the development, testing, and implementation of cutting-edge AI technologies. Your responsibilities will span across various aspects of AI engineering, including design, construction, and evaluation of AI models and algorithms, as well as collaborating with cross-functional teams to integrate AI solutions into real-world products and systems. In this role, you will have the opportunity to work on exciting research initiatives, assess the potential applications of emerging AI technologies, and showcase the value of these technologies to both IBM's businesses and strategic partners. You will be part of a diverse and inclusive team of researchers and engineers, working together to push the boundaries of AI innovation.

**Todas as nossas vagas são elegíveis para pessoas com deficiência ou reabilitadas.**

Required Technical and Professional Expertise

·  Strong programming skills in commonly used languages like Python or Java.
·  Demonstrated experience in developing, training, and testing deep learning models.
·  Background in LLMs and/or prompt engineering.
·  Strong communication skills.
·  Fluent English

Preferred Technical and Professional Expertise

·  Demonstrated experience working with NLP
·  Demonstrated experience with graph-based methods, graph neural networks, and/or graph transformers.
·  Demonstrated experience with training and inference of large language models.
·  Demonstrated experience with machine learning for source code.

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