Senior MLOps Engineer
1 tydzień temu
technologies-expected : Microsoft Azure CI/CD Docker TensorFlow Python Kubernetes PyTorch about-project : Our growing Data & AI team is looking for an experienced MLOps Engineer. Our mission is to optimize processes in our warehouse locations using AI, rapidly implement ideas, and create customer value. You will be responsible for the deployment, optimization and monitoring of machine learning models in our production environment, collaborating with Data Scientists, Data Engineers, and DevOps teams. If you're passionate about operationalizing ML models and working in a dynamic and innovative environment, you've come to the right place. responsibilities : Model Deployment: Efficiently deploy ML models into production environments. Monitoring and Maintenance: Continuously monitor model performance and set up automated retraining pipelines. Infrastructure Management: Manage and maintain cloud and on-premises infrastructure for model training and deployment. Collaboration: Work closely with Data Scientists, Data Engineers, and DevOps teams to integrate models into existing systems. CI/CD Pipelines: Build and maintain CI/CD pipelines for seamless model deployment. Data Management: Create and manage data pipelines, ensuring data is clean and accessible for model training. Security and Compliance: Ensure deployed models adhere to security best practices and compliance requirements. Optimization: Optimize model performance and infrastructure for efficiency and cost-effectiveness. Documentation and Reporting: Document deployment processes, model performance, and provide regular reports. requirements-expected : Academic Qualification: Degree in computer science, mathematics, engineering, or a related field. Professional Experience: At least 5 years of experience in a similar position as an MLOps Engineer or DevOps Engineer in the ML environment. Good knowledge of Python and experience with ML Libraries (e.g., TensorFlow, PyTorch, Scikit-Learn). Experience with Cloud Services (Azure) and infrastructure tools (e.g., Docker, Kubernetes, Terraform). Knowledge in building and deploying CI/CD Pipelines and version control Systems (Azure DevOps and Git). Familiarity with MLOps practices and tools (e.g., MLflow). Experience in Monitoring and Logging ML Models is an Advantage. Ability to make informed decisions about the tech Stack. Knowledge of logistics processes is an advantage to better understand the specific requirements and challenges of the industry. Fluent in English, both written and spoken. Experience with agile working methods and the desire to develop further in an agile team. offered : Permanent employment contract and long-term cooperation Private medical care Sport card co-financing Hybrid type of cooperation (minimum 1 day/month for candidates outside Warsaw area) benefits : sharing the costs of sports activities private medical care sharing the costs of foreign language classes sharing the costs of professional training & courses life insurance remote work opportunities integration events
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