Meta

Software Engineer - Machine Learning (Technical Leadership)

Meta Singapore

Software Development · 10,001+ employees

13 h ago
machine-learning Principal (10+ yrs) Full-time Singapore
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About the role

You will lead a world-class team of engineers and researchers to drive technical direction and develop new features across Meta's platforms. The role involves identifying new opportunities, resolving complex performance issues, and collaborating with organizational leaders to improve team performance.

What they look for

Machine Learning Technical Leadership Recommender Systems Ranking Deep Learning Gradient Boosting Machines Random Forests System Architecture Scalability Data Analysis Mentoring Cross-functional Collaboration Roadmap Planning AI Ethics Prompt Engineering Agent Orchestration

Requirements

Candidates must have 12+ years of programming experience or 8+ years with a PhD, along with a degree in a technical field. Proven experience in mentoring, cross-functional leadership, and applying machine learning models at scale is required.

Full description

Meta is seeking principal engineers to join our teams in building cutting-edge products that connect billions of people around the world. As a member of our team, you will assess complex technical problems, build new features, and improve existing products across various platforms, including mobile devices and web applications. Our teams are constantly pushing the boundaries of user experience, and we're looking for passionate individuals who can help us advance the way people connect globally. If you're interested in leading a world-class team of engineers and researchers to work on exciting projects that have significant impact, we encourage you to apply.

Responsibilities

  • Drive the team's goals and technical direction to pursue opportunities that make your larger organization more efficient
  • Effectively communicate complex features and systems in detail
  • Understand industry & company-wide trends to help assess & develop new technologies
  • Partner & collaborate with organization leaders to help improve the level of performance of the team & organization
  • Identify new opportunities for the larger organization & influence the appropriate people for staffing/prioritizing these new ideas
  • Lead long term technical direction and roadmap for large cross-company efforts
  • Suggest, collect and synthesize requirements and create an effective feature roadmap
  • Identify and resolve performance and scalability issues, and drive large efforts to reduce technical debt

Minimum Qualifications

  • Experience mentoring/influencing engineers across organizations
  • Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions
  • Experience communicating and working across functions to drive solutions
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • Experience driving large cross-functional/industry-wide engineering efforts
  • Proven track record of planning multi-year roadmap in which short-term projects ladder to the long-term goals
  • 12+ years of programming experience in a relevant language OR 8+ years experience with a PhD

Preferred Qualifications

  • Experience applying ML Models in a revenue (Ads or E-Commerce) or user facing product environment at scale (Matching or Demand Supply)
  • Experience with relevant algorithms such as Learning to Rank, Gradient Boosting Machines, Random Forests, Deep Learning and similar algorithms
  • Expertise in Recommender Systems, Ranking, Relevance, Personalization or adjacent fields of ML
  • Masters degree or PhD in Computer Science or a related technical field
  • Grasp of data structures and algorithms, including graph theory and optimization techniques
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

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