Meta

Research Scientist role focused on designing and developing novel benchmarks and evaluation methodologies for frontier AI capabilities within Meta Superintelligence Labs (MSL). The role involves measuring and understanding AI capabilities, influencing research direction, and collaborating with researchers and technical leadership. Requires a strong publication record and experience in machine learning research, particularly in evaluation and deep learning.

Research Scientist role focused on developing and implementing novel evaluations for frontier AI systems, shaping research direction and model development. Requires strong ML research background, experience with LLM/multimodal evaluation, and publication record.

Research Engineer role focused on building and curating benchmarks and evaluation environments for advanced AI models across text, vision, and audio. The role involves developing novel benchmarks, integrating existing ones, and creating scalable evaluation tooling to directly impact research direction and model development. Requires strong ML engineering and research skills, Python proficiency, experience with ML frameworks, and a track record of publications in relevant venues.

Research Scientist Manager to lead a team focused on measurement and evaluation of AI Assistants powered by foundation models. The role involves defining scientific strategy for evaluation, ensuring methodological rigor, and collaborating with product, engineering, and training teams to ensure reliability and trustworthiness at scale.

Director, Product Content Engineering at Meta, focused on driving evaluation efforts for LLM models across teams, leading sprints, and devising automation strategies. This role involves improving content discovery and distribution, working with ranking and delivery systems, and defining content strategies to enhance user experience. Requires technical expertise, data analysis, understanding recommendation systems, and cross-functional collaboration.

Meta's Finance team is seeking an AI Governance & Automation Manager to lead the rollout, operationalization, and optimization of their AI governance program. This role ensures AI adoption within Finance is compliant with SOX and other regulations, while enabling autonomy and efficiency. Responsibilities include program rollout, SOX compliance, framework optimization, defining system requirements for the AI governance platform, collaborating on its build and enhancement, developing continuous monitoring features, ensuring technology integration, reporting on program health, and driving adoption through training and change management. The role also involves staying current on AI technologies, regulatory landscapes, and influencing stakeholders across various functions.