Software Engineer II, Machine Learning, Risk Engineering

Etsy•New York, NY

1d•$153,000 - $199,000•Hybrid

About The Position

Etsy is hiring an Machine Learning Engineer II to join the Risk Engineering organization. Our team keeps Etsy a safe and trusted marketplace by building advanced and scalable ML technologies to detect and prevent risk and fraud. We are looking for passionate individuals that are committed to applying Machine Learning to deliver customer impact. This is a full-time position reporting to the Senior Engineering Manager, Risk ML. In addition to salary, you will also be eligible for an equity package, an annual performance bonus, and our competitive benefits that support you and your family as part of your total rewards package at Etsy. For this role, we are considering candidates based in the United States. Candidates living within commutable distance of Etsy’s Brooklyn Office Hub or in the San Francisco Bay Area may be the first to be considered. For candidates within commutable distance, Etsy requires in-office attendance once or twice per week depending on your proximity to the office. Etsy offers different work modes to meet the variety of needs and preferences of our team. Learn more details about our work modes and workplace safety policies here. Our work tackles pressing, real-world problems, including detection of transactional fraud, fake account creation, collusion fraud, and more. As a member of the product team, this role is an exciting opportunity to collaborate with experienced ML professionals on large-scale projects protecting millions of users.

Requirements

You have a Ph.D. degree in a quantitative field (e.g., computer science, industrial engineering, applied math, statistics) with machine learning research experience on risk/fraud applications, or a M.S. degree in related fields and 3+ years of industry experience in risk/fraud applications.
You have published at peer-reviewed conferences, such as ICML, KDD, SIGIR, WSDM, etc. or you have given talks/tutorials in the industrial conferences like Spark Summit.
You may have experience deploying, debugging, and improving machine learning models in large-scale production systems in public clouds (e.g., GCP, AWS, or Azure), with experience in Infrastructure as Code (e.g., Terraform)
You have experience or interest in building production risk/fraud detection systems, or general e-commerce systems.

Responsibilities

Build models to detect, and enforce on, bad actors on the platform.
Implement and compare supervised learning models (GBDT and DNNs), or ensembles of models, to improve key metrics, often with multiple competing objectives
Build unsupervised/semi-supervised anomaly detection models to identify emerging patterns with high precision.
Prototype, optimize, and productionize large-scale ML models that help deliver key results
Conduct A/B experiments to validate the efficiency of ML models and pipelines
Collaborate closely with product managers, ML engineers, full-stack engineers, and designers on a product team to protect ~100 million users
Push the state of the art and apply the latest advances in deep learning and other machine learning techniques to improve trust and safety on Etsy
Share impactful and innovative work in the wider ML research community, including presenting at top-tier ML/DS conferences such as: KDD, WSDM, WWW, Recsys, etc.