Machine Learning Engineer
Beeswax’s mission is to build great advertising software. Our product is an easy to use, massive scale and high availability advertising platform founded by industry veterans who worked together at Google. We offer our customers the most extensible and transparent advertising system in the world and process billions of transactions per second.
We are looking for a Machine Learning Engineer with an in-depth working knowledge of the latest in Machine Learning/Data Science technologies and cloud platforms to join our Optimization team.
In this role you’ll work on a wide range of computational challenges such as: CTR prediction, forecasting, bidding models, and delivery optimization. We practice an effective data science process that recognizes the uncertainty in explorations for ML solutions but also emphasizes an agile software engineering workflow. We use the most popular tools in the Python data science ecosystem and embrace innovation.
Our tech stack is always evolving to meet the challenges of the massive scale of transactions on which we operate. To manage the firehose of data coming in, we explore complex tradeoffs and carefully architect high performance distributed systems. Those in turn require elegant and thoughtfully designed interfaces to make the systems accessible to both our team and our customers.
- Contribute to data science projects and ensure they deliver business value
- Work with the Product and Engineering team to build data model pipelines to power customer-driven products
- Implement and test the latest research works
- BSc or above in a STEM (science, technology, engineering, mathematics) subject
- 2+ years of demonstrable experience with Machine Learning/Data Science
- Efficient in Python and SQL
- Good understanding of engineering best practices, agile (in Data Science) and version control
- Experience with out-of-core algorithms
- Effective collaboration with Product, Commercial team and Engineering team
- Strong understanding and experience in distributed ML frameworks, especially in Tensorflow
- Practical experience with Data Warehousing, especially Snowflake
- Practical experience with ML Platforms (e.g., AWS SageMaker, Kubeflow)
- Excellent academic or industrial track record
- Knowledge of the latest Machine Learning/Data Science technologies and cloud platforms (especially AWS)
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