Job Title-Sr Software Engineer- Machine Learning (805) Duration- 7 months Start date & Location May 20, 2025 - Dec 12, 2025

Senior Software Engineer, Machine Learning (805) Dates: May 20, 2025 - Dec 12, 2025

Python programing skills for machine learning applications in the risk/fraud domain are expected

TECHNICAL SKILLS

Must Have Airflow Credit risk management Excellent Python programming skills Fraud Detection Machine Learning Algorithms

Nice To Have BigQuery Dataflow (Apache Beam) Google Cloud Platform (GCP) for Machine Learning

Job Description:

Typical responsibilities of this role include: • Solve customer and business problems (protecting against seller fraud, transactional fraud, account takeover, fake accounts, etc.) using machine learning techniques like graph ML, deep neural networks, and anomaly detection. • Take ideas and scale them to millions to users. Develop and implement end-to-end plans, including idea generation, project planning, model development, production model serving, and ownership of model performance. • rchitect new and improve on existing ML systems, including building data architectures (e.g. large-scale graph data processing and storage), enabling faster and more robust model development, and improving model serving and orchestration. • Provide technical leadership on long-term strategy, roadmap, ML design, and system architecture. • Help to coach and mentor more junior team members. • Collaborate with team members and cross-team partners for problem identification, technical design/delivery, and product operationalization. • Share impactful and innovative work in the wider ML research community, including presenting at top-tier ML conferences such as: KDD, ICML, NeurIPS, etc. • Of course, this is just a sample of the kinds of work this role will require! You should assume that your role will encompass other tasks, too, and that your job duties and responsibilities may change from time to time at Etsy's discretion, or otherwise applicable with local law.

Requirements

Must-Haves • You have 3+ years experience building ML models in the fraud/risk management space. • Experience deploying, debugging, and fine-tuning machine learning models in large-scale production systems in public clouds, with experience in Infrastructure as Code. • You are comfortable with using git, Linux environments, dockers, and other tools for writing robust, production-ready code. • You have focused experience deploying models in production at scale like unsupervised anomaly detection, graph neural network, deep learning, natural language processing, or reinforcement learning.

Nice-to-Haves • Google Cloud Platform (GCP) experience is a plus