MLOps/LLMOps Engineer

About the role

As an MLOps/LLMOps Engineer at Bamboohr, you will play a crucial role in bridging the gap between machine learning development and operational deployment. Your expertise will be vital in ensuring that our machine learning models are not only built effectively but also integrated seamlessly into production environments. You will collaborate with data scientists, software engineers, and other stakeholders to optimize workflows and enhance the scalability and reliability of our machine learning solutions. This position offers an exciting opportunity to work in a fast-paced environment where innovation and continuous improvement are at the forefront of our mission.

Key facts

What you'll do

• Design and implement robust MLOps pipelines to automate the deployment and monitoring of machine learning models in production.
• Collaborate with data scientists to understand model requirements and translate them into scalable solutions that can be integrated into existing systems.
• Develop and maintain tools for model versioning, testing, and validation to ensure high-quality outputs.
• Monitor and troubleshoot production models, ensuring they perform optimally and addressing any issues that arise promptly.
• Implement best practices for CI/CD (Continuous Integration/Continuous Deployment) in machine learning workflows to streamline processes.
• Work with cloud platforms (such as AWS, Azure, or Google Cloud) to deploy and manage machine learning applications at scale.
• Create documentation and training materials to support team members and stakeholders in understanding MLOps processes and tools.
• Stay updated with the latest trends and technologies in MLOps and machine learning to continuously improve our practices and tools.
• Collaborate with cross-functional teams to gather requirements and feedback, ensuring that our solutions meet business needs effectively.
• Participate in code reviews and provide constructive feedback to peers to enhance code quality and team collaboration.
• Contribute to the development of internal tools and frameworks that improve the efficiency of machine learning operations.
• Assist in the onboarding of new team members by sharing knowledge and best practices related to MLOps and LLMOps.

Requirements

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.
• A minimum of 3 years of experience in MLOps or a related role, with a strong understanding of machine learning lifecycle management.
• Proficiency in programming languages such as Python or Java, with experience in libraries and frameworks commonly used in machine learning.
• Familiarity with containerization technologies like Docker and orchestration tools such as Kubernetes.
• Experience with cloud computing platforms (AWS, Azure, or Google Cloud) and their machine learning services.
• Strong understanding of CI/CD practices and tools, with experience in automating deployment pipelines.
• Excellent problem-solving skills and the ability to work independently as well as part of a team.
• Strong communication skills to effectively collaborate with technical and non-technical stakeholders.

Nice to have

• Experience with large language models (LLMs) and their deployment in production environments.
• Knowledge of data engineering practices and tools, including data pipelines and ETL processes.
• Familiarity with monitoring and logging tools to track model performance and system health.
• Experience with version control systems, particularly Git, for collaborative development.
• Understanding of security best practices in machine learning and data handling.

Skills & tools

• Proficient in Python, with a solid understanding of machine learning libraries such as TensorFlow, PyTorch, or Scikit-learn.
• Familiarity with data visualization tools and techniques to present model performance and insights.
• Experience with database management systems (SQL and NoSQL) for data storage and retrieval.
• Knowledge of Agile methodologies and project management tools to facilitate team collaboration.

Practical notes

• This position is based in Riyadh, and candidates should be prepared for a full-time commitment.
• Sponsorship for a work visa is available for qualified candidates, ensuring that we attract the best talent globally.
• The selected candidate will have opportunities for professional development and growth within the organization, contributing to exciting projects in the field of machine learning and data science.

META

Company: Bamboohr

Title: MLOps/LLMOps Engineer

Listed

location: Riyadh

Job type: Full-time

Apply URL: https://datascience.bamboohr.com/careers/119

Tags: Engineering