Requirements:

Bachelor’s degree or equivalent practical experience.
2 years of experience with software development in one or more programming languages such as C++, or 1 year of experience with an advanced degree.
1 year of experience with one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).

Nice to Haves:

Build, deploy, and iterate on machine learning models (including LLMs) to detect policy violations in Shopping content.
Develop and deploy scalable pipelines for high-quality training data curation, striving for gold-standard datasets and implementing frameworks for model evaluation and performance tracking.
Utilize and deploy Leverage Large Language Model (LLMs) including auto-raters and agents, to enhance merchant experience, operational accuracy and efficiency across multitude use cases such as managing escalations, reviewing user reports, merchant appeals, metrics generation and training data quality curation.
Collaborate with Product Managers, Policy Specialists to identify and implement opportunities to support business growth and consumer protection.
Contribute to the team's engineering excellence by maintaining and improving the reliability of the production system, participate in teams on call and contribute to code reviews, documentation, and overall system health.