Data Science and Machine Learning Engineer
3 weeks ago
We're expanding our Data Products team to drive success across Commercial, Customer, Finance, and Product domains by making our data available and usable in one place to deliver powerful data solutions that optimise performance and supercharge decision-making.
Our vision is to create the world's most rewarding experiences, and we're looking for an experienced ML Engineer to help us scale our capabilities to meet the needs of our team and our company's goals.
This role offers a unique opportunity to operate in a hybrid data science/ML engineering space, with an interest in platform/operations, and to contribute to the design, development, and deployment of our ML platform.
Key responsibilities include defining and implementing best practices for training, evaluating, and deploying machine learning models at scale, collaborating with software engineers, data engineers, and data scientists to develop end-to-end AI products & solutions, and extending and maintaining our self-service platform to help our data science teams quickly productionise models following MLOps best practices.
We're looking for someone with hands-on experience in data science and machine learning engineering, with a proven track record from design to deployment, and extensive knowledge of software development with Python, SOLID principles, and machine learning techniques, such as supervised and unsupervised learning, MLOps, and data engineering.
Practical knowledge of cloud platforms, such as AWS, Snowflake, GCP, or Azure, and experience with or equivalent to Snowflake Cortex, AWS Bedrock, AWS MSK, Snowpipe Streaming, Snowpark Container Services is also required.
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