Mlops
hace 5 días
The ML / MLOps Engineering team is responsible for the successful implementation and iteration of AI/ML solutions including providing architectural guidance and development support. Some of our focus areas include: developing reusable frameworks, code optimization and refactoring, scaling up ML solutions, and foreseeing and testing for common issues that may arise in production. We are looking for a highly capable Senior ML or MLOps Engineer with a strong Software Engineering and DevOps background. As a Senior MLOps Engineer, you will be embedded and supporting a revenue generation or cost optimization project, ensuring its success in production by improving the code, creating automated CI/CD testing, and developing frameworks that can be reused for other similar projects.
Activities:
Build, maintain, and document machine learning frameworks (python packages) used across multiple projects.
· Support a project team with Data Scientists, Business Stakeholders, Analysts, and Data Engineers.
· Develop reusable feature stores for rules-based and AI/ML models.
· Implement monitoring capabilities for model performance and effectiveness in production.
· Automate CI/CD testing and deployments incorporating MLOps best practices.
Skills:
-Bachelor's degree in software engineering, computer science, data science, mathematics, or a related field.
· 5+ years of overall experience in Data Analytics.
· 3+ years of experience with ML Engineering and/or ML Ops. Up to 2 years of Software Engineering or Data Engineering experience can also count towards this requirement.
· Sharp critical thinking skills and ability to learn and question complex processes and solutions.
· Experience building scalable machine learning systems and data-driven products working with cross-functional teams.
· Experience creating python packages
· Well-developed software engineering skills, including use of proper development, QA, and production environments, object-oriented programming, version control, and knowledge of multiple programming languages.
· Proficiency in Python and experience with common data analytics packages (e.g. Numpy, Pandas, Sklearn, PySpark).
· Proficiency in SQL and Azure
· Good communication skills and the ability to understand and synthesize requirements across multiple project domains.
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