MLOps Platform Engineer

We are seeking a highly skilled and motivated MLOps and LLMOps Platform Developer to join our innovative team. In this role, you will be responsible for developing and maintaining our machine learning operations (MLOps) and large language model operations (LLMOps) platforms. Your expertise in software development, platform engineering, and machine learning will be essential to drive the success of our cutting-edge projects.

Key Responsibilities:

• Design, develop, and maintain MLOps and LLMOps platforms to streamline machine learning workflows.
• Collaborate with data scientists, engineers, and other stakeholders to implement scalable and efficient platforms and AI/ML solutions.
• Understand and modify existing open source tools to meet platform need.
• Integrate CI/CD practices to ensure robust and reliable platform services.
• Optimize platform performance and scalability to handle large volumes of data and complex ML models.
• Implement security best practices to safeguard data and models.
• Provide technical support and troubleshooting for platform-related issues.
• Stay up-to-date with the latest advancements in MLOps, LLMOps, and related technologies.

Qualifications:

• Bachelors or Masters degree in Computer Science, Engineering, or a related field.
• Proven experience in software development and platform engineering.
• Strong knowledge of machine learning concepts and frameworks.
• Proficiency in programming languages such as Python, Java, or C++.
• Experience with cloud platforms (e. g. , AWS, GCP, Azure) and containerization tools (e. g. , Docker, Kubernetes).
• Familiarity with CI/CD tools and practices (e. g. , Jenkins, GitLab CI).
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills.

Preferred Qualifications:

• Understanding of AI/ML lifecycle, concepts, framework and development.
• Knowledge of distributed computing and big data technologies (e. g. , Spark, Hadoop).
• Familiarity with parallel computing and distributed computing concepts and tools(e. g Ray, ).
• Familiarity with kubernetes and kubernetes deployment.

Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. .

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