Machine Learning Engineer – Core Ads Ecommerce

Company: Meta Platforms, Inc.
Apply for the Machine Learning Engineer – Core Ads Ecommerce
Location: Chinatown
Job Description:

Machine Learning Engineer – Core Ads Ecommerce Responsibilities

  • Partner with product teams and other engineers to solve Shops Ads business problems through ML
  • Play a critical role in setting the direction and goals for a sizable team, in terms of project impact, ML system design, and ML excellence
  • Re-evaluate the tradeoffs of already shipped features/ML systems, and you are able to drive large efforts across multiple teams to reduce technical debt, designing from first principles when appropriate
  • Leading a team from a technical perspective to develop ML best practices and influence engineering culture
  • Be a go-to person to elevate the most complex online / production performance and evaluation issues, that require an in depth knowledge of how the machine learning system interacts with systems around it
  • Suggest, collect and synthesize requirements and create effective feature roadmap
  • Code deliverables that will tie the ML solutions you develop to our ad delivery stack

Minimum Qualifications

  • Experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical field
  • Experience with developing machine learning models at scale from inception to business impact
  • Knowledge developing and debugging in C/C++ and Java, or experience with scripting languages such as Python, Perl, PHP, and/or shell scripts
  • Experience demonstrating technical leadership working with teams, owning projects, defining and setting technical direction for projects
  • Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

Preferred Qualifications

  • Masters degree or PhD in Computer Science or a related technical field
  • Exposure to architectural patterns of large scale software applications

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Posted: June 4th, 2026