Senior Machine Learning Engineer

About the job Your Mission The Global Analytics & Data Products Team is looking for a Senior Machine Learning Engineer. As a key member of the MLOPS team, your mission is to put science into decision making through machine learning initiatives. Priorities can change in a fast-paced environment like ours, so this role includes, but is not limited to the following responsibilities:

• Developing, researching and implementing MLOps frameworks, tools and platforms for our Data Science projects
• Designing and implementing infrastructure for machine learning cloud services
• Creating microservices for task-specific AI cloud services
• Implementing solutions for monitoring model performance and triggering alerts
• Enhancing speed of delivery, automating Model Retraining, Model Monitoring, Model Versioning, improving quality/security of code, and optimizing processes
• Collaborating with the data platform team to create a feedback loop and improve the underlying data infrastructure
• Partnering with peers to ensure scalability, business continuity and appropriate turnaround time
• Working on a backlog of activities to raise MLOps maturity in the organization. Evolve our framework as new technologies and techniques emerge
• Proactively introduce a modern, agile and automated approach to Data Science

• Experience in converting data science prototypes for deployment into production purposes
• Record of designing and implementing scalable, performant data and machine learning pipelines, services, and products
• Understanding of distributed data systems and experience in using open source frameworks to build applications
• Be able to communicate collaboratively with Data Scientist, Infrastructure teams and client to understand requirements and scope
• Solid intuition when choosing the right ML/AI approaches to the problems given
• to influence non-technical peers and leadership to deliver substantive change
• for less experienced colleagues and guardian of good standards

• MSc / MEng degree in Statistics, Computer Science, Automatic Control, STEM, Engineering or a related discipline
• Experience, coding in Python or other languages
• Experience in the operationalization of Data Science projects (MLOps) using Databricks+MLFlow,
• Hands-on experience with PySpark and SQL
• Working proficiency in English

• Multidimensional skill set: data science, experimentation, AI, statistics, engineering, etc.
• Experience in front- and backend design and development (leveraging Django, Node.js, Streamlit or similar)
• experience with containerization (using Kubernetes, Docker)
• in CI/CD/CT pipeline implementation
• overview of AWS services to design cloud solutions
• knowledge in shell scripting and networking