Description

In this role, you will design and maintain MLOps pipelines while managing the entire ML/AI model lifecycle. Collaborating with data scientists and cloud teams will ensure that solutions are secure, scalable, and compliant, making a significant impact on the transformation into a Data-&-AI-first player.

Requirements

• •Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field
• •Proven professional experience as a Machine Learning Engineer, MLOps Engineer, Data Engineer, or in a similar role
• •Professional experience across multiple areas of machine learning, including classical ML, deep learning, and Generative AI
• •Experience integrating GenAI / LLMs into scalable, business-critical solutions
• •Strong hands-on experience in cloud engineering, preferably on Google Cloud Platform
• •Proficiency in Python and SQL, with experience using common ML frameworks such as TensorFlow, PyTorch, and scikit-learn
• •Experience deploying and operating ML models in production, covering the full lifecycle from data preparation to model re-training
• •Hands-on experience with containerization and orchestration technologies
• •Knowledge of CI/CD pipelines and infrastructure automation
• •Experience working with large-scale data processing systems and applying data engineering best practices
• •Strong ability to collaborate cross-functionally and contribute to discussions with diverse stakeholders

Tasks

• •Design end-to-end MLOps pipelines using cloud-native services
• •Implement and maintain MLOps pipelines
• •Manage the complete ML/AI model lifecycle
• •Monitor model performance and versioning
• •Deploy ML/AI models effectively
• •Collaborate with data scientists to create production-ready solutions
• •Work closely with cloud and platform teams for security and scalability
• •Ensure regulatory compliance in ML operations
• •Troubleshoot issues in ML pipelines and cloud infrastructure
• •Resolve deployment lifecycle challenges
• •Support discussions with non-technical stakeholders on solution definitions

Tools & Technologies

Benefits