About this role

Contribute to designing, scaling/building, evaluating, integrating, shipping, and refining reward signals for recommendations by hands-on ML development.
Lead collaborations and align across Personalization to integrate and A/B test mid-term signals in various recommendation systems.
Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization.

You have a background in machine learning, enjoy applying theory to develop real-world applications, with experience in statistics and optimization, especially in sequential models, transformers, generative AI and large language models, and relevant fine-tuning processes.
You have hands-on experience with large cross-collaborative machine learning projects and managing stakeholders.
You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages.
You have some experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, or even our open source API for it
Scio, and cloud platforms like GCP or AWS.
You care about agile software processes, data-driven development, reliability, and disciplined experimentation.

Machine Learning Engineer II

Key skills