Position Title - ML(Machine Learning) Engineer
Location - Austin, TX
This job requires 80-90% coding or coding-related tasks every day.
Machine learning, Java/Python, Cloud-native applications, SQL, Spark/Hadoop/BigQuery & Graph analyzing/processing tools.
Hive, RankLib, Learning To Rank, PyTorch, Tableau, Kubernetes, Dataproc, Docker, Cloud Foundry, TensorFlow, CUDA, Airflow, Beam, SPARQL, RDF, Solr, Lucene, DataFrame, Pandas, Keras, scikit, Concourse, Matplotlib, neural networks, deep learning.
Object-oriented programming, functional programming, familiarity with cloud tools.
To determine the most relevant products for a given customer question from a 2.5M catalog is not an easy task. We engage machine techniques in several internal groups within the search team (e.g., understanding the customer question, enriching the product catalog, and sorting the products).
The machine learning engineer will quickly iterate on the following three steps:
1) Based on data analysis, form a hypothesis on how to improve the customer search experience;
2) Test the hypothesis
3) Deploy the model to production, if the evaluation turns out to be good.