Description:

The Personalization team, part of the Machine Learning Chapter and Engineering Department, focuses on implementing algorithms that utilize personalization signals to optimize business KPIs such as revenue and conversions.
The team emphasizes metrics over features, enhancing search, browse, and recommendation products with powerful personalization capabilities that deliver value to customers.
As a member of the Personalization team, you will employ advanced analytical, engineering, and machine learning techniques on big data to develop and scale personalization algorithms.
You will tackle challenges such as building and deploying robust ML systems for personalized product discovery experiences, driving research initiatives to adopt innovative approaches, and conceptualizing new personalization features that meet customer needs and enhance business KPIs.
Collaboration in architectural discussions and optimization of the system architecture within the Personalization domain is also a key responsibility.

Requirements:

You must be data-driven and customer-focused, capable of translating insights into data-driven hypotheses and engineering solutions that provide business value, with a passion for experimentation and using customer feedback.
A background in personalized recommendation systems, ranking models, or search relevance is required.
Proficiency in machine learning with hands-on experience in applying modern personalized architectures is essential.
You should have proven experience in building and deploying production ML systems and using A/B testing to validate their effectiveness.
Excellent Python skills, experience with at least one deep learning framework, proficiency in SQL, and comfort with big data tools such as Spark, Presto/Athena, and Hive are necessary.
Experience with data pipeline orchestration tools (e.g., Airflow) for automating ML workflows is required.
Effective communication skills are essential for clearly explaining complex technical concepts and data insights to both technical and non-technical audiences.

The compensation package includes a base salary range of 90-110k USD, stock options, and a work-from-home bonus.
The position is fully remote, allowing you to choose your living location.
A work-from-home stipend is provided to ensure you have the necessary resources to set up your home office.
New employees will receive Apple laptops.
There is a training and development budget for every employee, refreshed annually.
Qualified employees are entitled to parental leave.
You will have the opportunity to work with intelligent colleagues who will support your growth and enable you to make a meaningful impact.