Machine Learning Engineer
Digital & Technology Team (D&T) is an integral division of HEINEKEN Global Shared Services Center. We are committed to making Heineken the most connected brewery. That includes digitalizing and integrating our processes, ensuring best-in-class technology, and embedding a data-driven culture. By joining us you will work in one of the most dynamic and innovative teams and have a direct impact on building the future of Heineken!
Would you like to meet the Team, see our office and much more? Visit our website: Heineken (heineken-dt.pl)
Your responsibilities would include:
1. Machine Learning Model Development:
- developing production-level ML libraries and algorithms for existing and future products
- writing code to enhance machine learning capabilities
- reviewing code developed by other team members, providing feedback and insights.
2. Infrastructure Development and Management:
- developing and improving the infrastructure used for building and deploying machine learning models
- improving pipelines for data ingestion and feature engineering
- designing and implementing processes for end-to-end management of machine learning pipelines.
3. Data Processing and Machine Learning Systems:
- having hands-on experience with building data processing pipelines, large-scale machine learning systems, and big data technologies (e.g., Hadoop, Spark).
- developing and implementing scalable and efficient model training workflows on a large scale
- fluency in Python programming and working knowledge of Databricks and PySpark
- fluency in extracting information from databases and good SQL skills.
4. Software Development Skills:
- demonstrating very good coding skills and software development experience
- understanding fundamental data science concepts and have experience with common tooling and packages used for machine learning
- possessing knowledge of application architectures and design patterns
- applying professional software engineering and best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- writing clean, efficient, documented, and scalable code.
You are a good candidate if you have:
- at least 2 years of experience applying Machine Learning in the industry
- experience in writing production code for machine learning models
- experience related to using ML infrastructure at scale
- very good coding skills and software development experience
- fluency in Python programming.
- working knowledge of Databricks and PySpark
- end-to-end hands-on experience with building data processing pipelines, large-scale machine learning systems, and big data technologies (e.g., Hadoop, Spark)
- fluency in extracting information from databases and good SQL skills
- understanding of fundamental data science concepts and experience with common tooling and packages used for machine learning
- knowledge of application architectures and design patterns
- knowledge of professional software engineering and best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- ability to write clean, efficient, documented, and scalable code.
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Test Engineer, Testing, Database, SQL, Software Engineer, Engineering, Technology