We are looking for a software engineer with data/backend experience to contribute to our efforts focused on data cleaning, data understanding, developing features for machine learning models, benchmarking model performance, automating the configuration and optimization of machine learning models, and putting machine learning models into production. You will have the opportunity to work with state-of-the-art technologies on large data sets. You’ll have exposure to all aspects of our machine learning infrastructure and the chance to define and engineer solutions that will underpin millions of transactions per year.
The technologies currently being used in the machine learning infrastructure are Python, Pandas, numpy, TPOT, scikit-learn, XGBoost, Azure SQL DB, Azure Blob Storage. The technologies that we are considering using include Azure Cosmos DB, Spark, Databricks, auto-sklearn, and PyTorch.
- 5+ years experience of software engineering experience focused on data engineering, backend engineering, or roles working on software that primarily focuses on any kind of data heavy pipeline / toolchain (build toolchain, content pipeline, streaming, etc.).
- Demonstrated experience with the complete software development lifecycle is required.
- The ability to learn quickly in a self-directed manner.
- A willingness to work in Python.