Summary:

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).

Required Skills:

Engineering Manager (ML), Similarity Detection Match Quality Responsibilities:

1. Be both highly technical and an effective people manager

2. Lead teams that deliver on multiple projects of increasing dependencies in an ambiguous or high-impact area

3. Work with your team and XFN partners to define and influence strategy

4. Be a subject matter expert in an ML domain

5. Drive roadmap creation and execution

6. Collaborate with various functions, drive engineering initiatives and have an impact at an organisational level

7. Participate in technical design

8. Measure the impact of your team and set clear expectations and goals

9. Work effectively with XFN partners and stakeholders to set and achieve optimal outcomes

10. Partner with leadership to influence and drive org design, contribution and prioritization

Minimum Qualifications:

Minimum Qualifications:

11. Proven track record of supporting technical teams

12. Strong problem solving skills and background in coding

13. Demonstrated ability to manage technical teams

14. Knowledge of growing teams and/or organisations

15. Experience supporting machine learning teams

16. BS / MS in Computer Science (In lieu of degree, relevant work experience)

Preferred Qualifications:

Preferred Qualifications:

17. Experience with developing and operating models at large scale

18. Understanding of end-user trust and safety or of application integrity

19. Knowledge of content embeddings or content classification

20. PhD in Computer Science

Industry: Internet