For our client – international software company focusing on a project in the scientific/pharmaceutical industry – we are looking for skilled Machine Learning Operations.
• Design, build and maintain the ML CI/CD pipelines that automate data collection, data analysis, experimentation, model training and validation, model serving and monitoring in production.
• Develop systems, tools, & processes to deploy machine learning models built by the Data Science team into production
• Manage ETL and machine learning model lifecycle: develop, deploy, monitor, maintain, and update data and models in production.
• Stay up to date with new technologies and determine how to incorporate these into future platform capabilities
• Build strong relationships with cross-functional team members and business stakeholders
• 3+ years’ in a Data Scientist or ML Ops role.
• Experience building, deploying and maintaining ML models in production. Experience with MLOps tools such as ModelDB, MLFlow and Kubeflow.
• Experience managing end-to-end machine learning pipeline from data exploration, feature analysis and selection, model building, bootstrapping and final deployment.
• Understanding of various aspects of data preparation, feature engineering model training
• Proficiency with data analysis languages and tools such as Python/Jupyter or R
• Experience collaborating with cross functional teams
• AWS or Azure Cloud
• Design and document APIs leveraging a standard API documentation framework (Swagger)
• Life Science experience preferred, but not required
• Annual bonus
• Flexible working schedule and 3 sick days per year
• Outstanding career and development prospects
• Company stocks program
• Exciting company culture which stands for integrity, intensity, involvement and innovation
• The opportunity to work with a truly global organization
Our client is international software company focusing on a project in the scientific/pharmaceutical industry.