Software Engineer, Machine Learning

Skills

In this role you will have the opportunity to work with our machine learning systems that impacts our ads delivery system including candidate retrieval user engagement modeling and ad experience on Etsy.com and the Etsy app. In addition to expanding our machine learning systems you will work closely with other machine learning engineers and our product analytics partners to help drive product and customer impact.

Description

Etsy is seeking a Senior Engineer for our Ads Recs Quality team, one of the machine learning engineering teams for Etsy Ads, Etsy's onsite ad platform.



Etsy Ads is used by our smallest and largest sellers to grow their businesses and it is one of the major revenue streams for Etsy. The AdsRecs Quality team focuses on determining which listings a buyer should be shown using machine learning techniques in order to maximize relevance, seller return, and Etsy revenue. This includes building machine learning systems designed to retrieve the most relevant ads for our buyers across a range of advertising surfaces throughout the buyer's journey.

Responsibilities

• Solid engineering & coding skills and proficiency in at least one programming language of Python, Scala, or Java.
• Experience with writing scalable and performant data pipelines on distributed systems
• Familiar with machine learning techniques and applications
• Nice-to-Haves
• Hand-on experience in machine learning frameworks & technologies such as Tensorflow / TFX, Pytorch, Kubeflow.
• Experience with the ML lifecycle: training, deployment, monitoring, debugging and iterating on production machine learning systems
• Familiar with Google Cloud Platform and products such as Dataflow, Vertex AI

Educational Requirements

• Experience in machine learning techniques, pipelines and applications
• Experience with writing robust, idiomatic and easy-to-understand backend code (Python, Java, Scala).
• Experience writing scalable and performant data pipelines on distributed systems (e.g. Hadoop, Spark) - preference in candidates with experience in Airflow
• Nice To Have
• Experience with cloud platforms like GCP or AWS
• Familiar with ML lifecycle: training, deploying, monitoring, debugging, and iterating on production machine learning systems.
• Familiar with modern machine learning frameworks such as TensorFlow or Pytorch.