Staff Research Engineer, MRS AI

Meta is seeking a Staff Software Engineer to join the MRS AI Knowledge team, where we build horizontal ML solutions and AI infrastructure to improve the performance of our recommendation systems across Instagram, Facebook, Threads, Search, IG Reels, FB Reels, and more. In this role, you will lead the design and development of cutting-edge ML technologies — including AI Agents, LLMs, Graph Learning (GNN, GCN, Random Walk), and data optimization techniques — to power video, photo, audio, user, and text understanding and matching at scale. You will drive technical strategy, mentor other engineers, and partner closely with research and product teams to deliver meaningful product impact.

Responsibilities

• Lead the design and implementation of recommendation system models and AI infrastructure based on state-of-the-art ML technologies including AI Agents, LLMs, Graph Learning (GNN, GCN, Random Walk), and CNN/SNN/TTSN architectures
• Build and optimize ML solutions for video, photo, audio, user, and text understanding and matching across Meta's recommendation products
• Drive data optimization initiatives including reweighting, sampling, denoising, and augmentation to improve model performance
• Engage in and contribute meaningfully to projects' direction and roadmap, helping shape the technical vision for the team
• Build deep understanding of Meta's recommendation products and content ecosystem, and effectively incorporate that knowledge into solution designs
• Hold yourself and others accountable for engineering, ML, and data excellence across all deliverables
• Communicate effectively with team and cross-functional partners to unblock work streams and deliver product impact
• Mentor other engineers on ML system design, recommendation system architecture, and engineering best practices
• Drive experimentation frameworks for evaluating model quality, including designing evaluation metrics and making data-informed decisions on model selection and deployment
• Champion privacy-by-design and responsible AI principles in the development of ML models and recommendation systems

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 8+ years of experience in software engineering with a focus on natural language processing, computational linguistics, or language model systems
• Experience designing and shipping production NLP systems such as text classification, named entity recognition, semantic parsing, machine translation, or language generation at scale
• Experience leading major technical initiatives end-to-end, including architecture design, cross-team coordination, staged rollout using feature flagging and A/B testing frameworks, and post-launch monitoring
• Experience with distributed systems and large-scale data processing pipelines for training or serving language models
• Experience communicating technical decisions and trade-offs in writing to both technical and non-technical stakeholders, including design documents and cross-functional reviews Experience building evaluation infrastructure and benchmark suites for measuring language model quality, fairness, and robustness across diverse user populations
• Contributions to published NLP research or open-source language engineering projects
• Experience with large language model fine-tuning, alignment techniques, retrieval-augmented generation, or multilingual NLP systems
• Experience applying AI-assisted development tools to accelerate engineering workflows, code review, and system design in an NLP or ML engineering context