[royston@prod] ~/public_html

royston@prod:~$ whoami

Royston Monteiro

role: Staff Software Engineer (IC6)
loc:  San Francisco Bay Area

I build backend systems for large-scale ML and generative AI products — real-time inference under production latency, cost, and integrity constraints, evaluation infrastructure for generative models, and ML internationalization for low-resource markets. Fifteen-plus years across high-stakes domains: risk systems on Wall Street, and consumer AI (currently at Meta) serving hundreds of millions of people daily.

Portrait of Royston Monteiro
100M+
daily users on surfaces I build for
15+ yrs
building production systems
5
shipped product families

royston@prod:~$ cat experience.log

2017 → now

Staff Software Engineer @ Meta

Technical lead for GenAI Suggested Replies, Contextual Replies, Notifications, and Feedback workstreams.

earlier

Risk-Systems Engineering @ Morgan Stanley · Goldman Sachs · Oracle

Counterparty-risk (CVA/RWA) and CCAR stress-testing infrastructure; grid-computing optimization.

education

M.S. in Computer Science @ New York University

royston@prod:~$ ls selected-work/ --featured

├── genai/suggested-replies

Multimodal GenAI Suggested Replies

Backend lead — integrating large language and visual content-understanding models into a real-time consumer product. → shipped under production latency, cost, and integrity constraints at consumer scale.

├── eval/launch-gating

Quality-Evaluation & Launch-Gating Systems

Structured human evaluation at scale, secondary-LLM prompt-quality pipelines, and per-suggestion engagement measurement. → the gate GenAI features pass before launch.

├── i18n/conversational-suggestions

Internationalization of Conversational Suggestions

Led integrity recovery and expansion of ML-driven suggestion systems to non-English markets. → translation-pathway architecture for low-resource deployment.

├── infra/autogen

Interactive Overlays & “Autogen”

Server-side interactive-overlay generation and the code-generation framework behind interactive story feedback formats.

└── shipped/

Candid Stories · Stories Archive · Feedback Formats

Backend lead for Candid Stories (dual-camera format, 2022); built the Stories Archive with its Activity Log and data-portability layer; shipped interactive polls, reactions, and sticker feedback.

royston@prod:~$ history | grep -i "service"

royston@prod:~$ ./reviewing-interests --list-flags

multimodal-ml-systems conversational-ai llm-evaluation quality-measurement production-genai-infra ml-internationalization low-resource-deployment ai-safety consumer-integrity