Introduction
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

• You will play a crucial role in enhancing our machine learning infrastructure. The ideal candidate will have a solid foundation in DevOps practices and tools, enabling seamless integration and deployment of machine learning models. You will be responsible for automating workflows, managing CI/CD pipelines, and ensuring the reliability and scalability of our ML applications.

• In addition to your DevOps skills, you should possess a strong understanding of machine learning concepts, including AI inferencing and benchmarking techniques. You will collaborate closely with AI researchers and engineers to optimize model test performance and streamline deployment processes. If you are passionate about bridging the gap between development and operations in the rapidly evolving field of AI, we'd love to hear from you.
  
  Todas as vagas são elegíveis para pessoas com deficiência ou reabilitadas.

• Required Skills:

• 1-DevOps Expertise

• Proficient in CI/CD tools (e.g., Jenkins, GitLab CI)

• Experience with containerization (Docker, Podman, Kubernetes)

• 2-Machine Learning Knowledge

• Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch)

• Experience with AI inferencing and deployment of LLM models

• 3-Scripting and Programming

• Proficient in scripting languages (e.g., Python, Bash)

• Experience with at least one programming language (e.g., Java, Go, C++)

• 4-Version Control

• Proficient in Git and GitHub for version control and collaboration
• Fluent English

• Preferred Skills:

• 1-LLM (Large Language Model) Expertise

• Understanding of LLM architectures (e.g., GPT, BERT) and their applications

• Experience fine-tuning and deploying LLMs in production

• 2-OpenShift Architecture

• Understanding of OpenShift components (e.g., nodes, pods, services, routes)

• 3-Kubernetes Knowledge

• Familiarity with Kubernetes concepts and APIs, as OpenShift is built on Kubernetes

• 4-Monitoring and Logging

• Familiarity with monitoring tools (e.g., Prometheus, Grafana) and logging systems (e.g., ELK Stack)

• 5-Collaboration Tools

• Experience with Agile methodologies and tools (e.g., Jira, Trello)

• 6-Soft Skills

• Strong communication and teamwork abilities

• Problem-solving mindset with attention to detail