Machine Learning Engineer II, Fulfillment

About the role

Etsy is the global marketplace for unique and creative goods. The Machine Learning Engineer II will join the Fulfillment ML team, which owns the machine learning that powers Etsy's shipping and delivery experience, including models for Estimated Delivery Date, shipping price prediction, transit‑time modeling, and delivery‑risk signals. The role combines ML platform engineering with hands‑on applied ML work: building and operating the pipelines, orchestration, and tooling that take models from training through validation, promotion, and inference in production, and partnering with senior teammates on model evaluation, backtests, tuning, and readiness reviews.

Responsibilities

• Build and maintain the training, validation, promotion, and batch‑inference pipelines that put models into production and keep them healthy there.
• Write and extend Airflow DAGs within the templatized MLOps framework – training, inference, and validation workflows across staging, shadow, and production environments.
• Partner with teammates on the applied ML side – running backtests, tuning model outputs to hit business targets (on‑time delivery rate, cost, accuracy), and supporting seasonal readiness reviews.
• Contribute to model migrations onto the internal ML platform – wiring up model configs, feature pipelines, postprocessors, and inference runners alongside the teammates who design the models.
• Triage and debug production incidents that affect model‑driven surfaces (e.g., delivery estimates on Cart/Checkout or shipping prices in Search results), and coordinate fixes with partner teams.
• Improve observability – dashboards, retrain trending, data‑quality tags, and alert hygiene – so problems are easier to spot before they reach buyers or sellers.
• Write clear PRs, small‑medium design docs, and runbooks so what you learn becomes durable for teammates.
• Take part in the team’s on‑call rotation for model‑health and data‑quality alerts, ramping in gradually with senior support and clear runbooks.

Requirements

• 1‑3 years of professional experience building and shipping production ML systems (internships and academic research projects that shipped can count).
• Strong Python skills with a good sense for code hygiene, testing, and reviewing your own work before it lands.
• Exposure to batch data pipelines and ML orchestration (Airflow, Kubeflow, Dagster, Prefect, or similar).
• Comfortable with SQL and at least one cloud data warehouse (BigQuery, Snowflake, Redshift) – or ready to ramp quickly.
• Understanding of the ML lifecycle sufficient to reason about model behavior with teammates (training data, evaluation metrics, validation splits, and what it takes to put a model into production).
• Produce clear, testable, and maintainable code.
• Eager to be mentored, receptive to feedback, and comfortable growing inside an established codebase.
• Mindful of the impact your work has on Etsy buyers and sellers.

Skills

• Prior experience with PyTorch or another deep learning framework.
• Exposure to distributed compute (Spark, Ray, or Dask).
• Experience contributing to orchestration or feature pipelines.
• Prior experience in e‑commerce, shipping, or logistics problem spaces.

Benefits

• Equity package.
• Annual performance bonus.
• Competitive benefits that support you and your family.

Pay

• Geo‑1 (NYC metro, San Francisco Bay Area, Seattle metro): $156,000.00 – $210,000.00 USD Annual.
• Geo‑2 (all other U.S. locations): $140,000.00 – $190,000.00 USD Annual.

Schedule

For candidates within commutable distance of Etsy’s Brooklyn Office, the expectation is to work in the office once or twice per week. Remote candidates outside commutable distance may be considered on a case‑by‑case basis, with the expectation of occasional travel to the office.