Job
Description
As a member of the Agoda team, you will play a crucial role in leading the design, development, and implementation of on-premises MLOps solutions that support the delivery of machine learning models. Your responsibilities will include collaborating with data scientists and software engineers to build scalable and efficient data pipelines and model training and deployment systems. Additionally, you will develop and maintain monitoring and management tools to ensure the reliability and performance of our on-premises MLOps infrastructure. Your expertise will be key in working with stakeholders across the organization to understand their machine learning needs and requirements, and to develop MLOps solutions that meet those needs. Staying up-to-date with the latest trends and technologies in MLOps, LLMOps, machine learning, and artificial intelligence is essential, as you will be expected to share your knowledge with the team to help Agoda stay at the forefront of the field. Mentoring junior team members and assisting in their skills and expertise growth in MLOps will also be part of your role. Troubleshooting and debugging user issues will be another important aspect of your responsibilities. **Key Responsibilities:** - Lead the design, development, and implementation of on-premises MLOps solutions - Collaborate with data scientists and software engineers to build scalable data pipelines and model training systems - Develop monitoring and management tools for on-premises MLOps infrastructure - Understand stakeholders' machine learning needs and develop solutions to meet those needs - Stay updated with the latest trends in MLOps and share knowledge with the team - Mentor junior team members in MLOps - Troubleshoot and debug user issues **Qualifications Required:** - 5+ years of experience in MLOps, Software engineering, Data engineering, or related field - Strong programming skills in Java, Scala, Python, or Kotlin - Excellent communication and collaboration skills - Value code simplicity and performance If you have an understanding of ML Projects lifecycle, experience with MLOps platforms like Kubeflow or MLFlow, familiarity with ML frameworks such as scikit-learn, LGBM, Tensorflow, PyTorch, experience with Big Data tools like Spark, S3, Hadoop, knowledge of containerization and container orchestration technologies like Docker and Kubernetes, experience with DevOps and CI/CD practices, and a passion for the engineering behind machine learning, then it would be great for the role. Additionally, experience in designing and building MLOps infrastructure, including data pipelines, model training and deployment systems, and monitoring and management tools will be beneficial for succeeding in this position. As a member of the Agoda team, you will play a crucial role in leading the design, development, and implementation of on-premises MLOps solutions that support the delivery of machine learning models. Your responsibilities will include collaborating with data scientists and software engineers to build scalable and efficient data pipelines and model training and deployment systems. Additionally, you will develop and maintain monitoring and management tools to ensure the reliability and performance of our on-premises MLOps infrastructure. Your expertise will be key in working with stakeholders across the organization to understand their machine learning needs and requirements, and to develop MLOps solutions that meet those needs. Staying up-to-date with the latest trends and technologies in MLOps, LLMOps, machine learning, and artificial intelligence is essential, as you will be expected to share your knowledge with the team to help Agoda stay at the forefront of the field. Mentoring junior team members and assisting in their skills and expertise growth in MLOps will also be part of your role. Troubleshooting and debugging user issues will be another important aspect of your responsibilities. **Key Responsibilities:** - Lead the design, development, and implementation of on-premises MLOps solutions - Collaborate with data scientists and software engineers to build scalable data pipelines and model training systems - Develop monitoring and management tools for on-premises MLOps infrastructure - Understand stakeholders' machine learning needs and develop solutions to meet those needs - Stay updated with the latest trends in MLOps and share knowledge with the team - Mentor junior team members in MLOps - Troubleshoot and debug user issues **Qualifications Required:** - 5+ years of experience in MLOps, Software engineering, Data engineering, or related field - Strong programming skills in Java, Scala, Python, or Kotlin - Excellent communication and collaboration skills - Value code simplicity and performance If you have an understanding of ML Projects lifecycle, experience with MLOps platforms like Kubeflow or MLFlow, familiarity with ML frameworks such as scikit-learn, LGBM, Tensorflow, PyTorch, experience with Bi
