MACHINE LEARNING ENGIENEER II (REMOTE)

Role overview Join a product team building and operating machine learning features embedded in software products. The role covers collaborative solution design and implementation as well as production readiness: testing resilience, monitoring service performance, supporting users, and improving models and systems over time. Work may also include data engineering and helping other teams adopt machine learning practices.

Responsibilities - Pair with product, UX, and engineering colleagues to build secure, reliable, scalable machine learning solutions. - Turn user stories into clear, testable work and follow quality and change-control practices. - Write code or scripts to automate infrastructure, monitoring, and tests, including resilience testing. - Configure software and commercial products to meet changing business needs. - Build dashboards, logging, alerts, and response processes to surface issues proactively. - Support production applications and monitor service objectives, capacity, performance, data flows, and prediction quality.

Requirements - At least 18 years of age and legally permitted to work in the United States. - The posting identifies one to three years of relevant experience as preferred. - Ability to work with a product team on software delivery, testing, or production support. - Overnight travel may be required, typically 5% to 20% of the time.

Nice to have - Python, SQL, Git, Linux or Unix, and data engineering experience with platforms such as BigQuery. - Familiarity with machine learning methods and tools, including forecasting, clustering, anomaly detection, neural networks, statistics, Jupyter, Pandas, scikit-learn, TensorFlow, or PyTorch. - Exposure to Google Cloud machine learning services, Node.js, web technologies, REST APIs, and CI/CD. - Understanding of production system concerns such as availability, recovery, performance, efficiency, and security.

Benefits and work setup The listing describes an indoor work environment, mostly seated with opportunities to move around. A pay range is provided for certain U.S. locations, with amounts varying by location.