Have you ever wondered how Meta moderates billions of posts, ads, comments, photos, and videos shared every day? How technology empowers our reviewers so they can remove election misinformation, hate speech, or health hoaxes at scale?
Media Match Service (MMS) is the system at the heart of automatic moderation and our first line of defense. MMS is one of the 32 Meta Shared Systems, with ~70 internal teams using it to automatically handle harmful or illegal content. As a result, MMS accounts for >30% of making Meta products safe and inclusive by finding accurately and quickly all instances and derivatives of a given piece of content (photo, video, audio, text, post, ad) across all Meta apps. See MMS Product Overview and MMS Technical Primer for more details.
MMS is built by the Similarity Detection (SD) org in Integrity (XI) using Hack, C++, and Python. SD is based in London, UK, and spans 3 teams with 29 engineers (E4 to E6) and 9 XFN (PM, TPM, SPM, DS, DE, PD). The SD Match Quality (SDMQ) team consists of 7 MLEs (E4-6) and has partial product and data science support. The team owns the algorithms that power MMS. Specifically, we develop and optimise uni- and multi-modal similarity classifiers, embeddings, and indexing algorithms for performance, scale, and wide applicability (see 3-yr MMS Product Strategy.) In our quest, we collaborate extensively with partner teams of Meta scientists and applied researchers (see Similarity Research Group).
Engineering Manager (ML), Similarity Detection Match Quality Responsibilities
- Be both highly technical and an effective people manager
- Lead teams that deliver on multiple projects of increasing dependencies in an ambiguous or high-impact area
- Work with your team and XFN partners to define and influence strategy
- Be a subject matter expert in an ML domain
- Drive roadmap creation and execution
- Collaborate with various functions, drive engineering initiatives and have an impact at an organisational level
- Participate in technical design
- Measure the impact of your team and set clear expectations and goals
- Work effectively with XFN partners and stakeholders to set and achieve optimal outcomes
- Partner with leadership to influence and drive org design, contribution and prioritization
Minimum Qualifications
- Proven track record of supporting technical teams
- Strong problem solving skills and background in coding
- Demonstrated ability to manage technical teams
- Knowledge of growing teams and/or organisations
- Experience supporting machine learning teams
- BS / MS in Computer Science (In lieu of degree, relevant work experience)
Preferred Qualifications
- Experience with developing and operating models at large scale
- Understanding of end-user trust and safety or of application integrity
- Knowledge of content embeddings or content classification
- PhD in Computer Science
About Meta
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics. Meta is committed to providing reasonable support (called accommodations) in our recruiting processes for candidates with disabilities, long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support. If you need support, please reach out to
accommodations-ext@fb.com.
