Meta currently has 129 active AI-related job listings. The hiring is most concentrated in the application stage, representing 22% of the roles, followed closely by agents at 20% and pre-training at 16%. Research is the dominant function, with 63 roles, followed by Engineering with 52. The majority of these positions are located in the United States. Frequent tech tags include agent_orchestration, frontier_research, and multimodal. Over the last 30 days, Meta posted 18 new AI roles, a 31% decrease compared to the previous 30-day period.
Currently tracking 125 active AI roles, up 55% versus the prior 4 weeks. Primary focus: Ship · Research.
Meta currently has 140 active AI-related roles in our index. The most common open titles are: Business Support Engineer (5), AI Research Scientist, Robotics (3), Business Engineer, Business AI (3), Software Engineer, Systems ML (3), AI Research Scientist, VLM (vision language models) (2). Most positions are in Engineering and Research.
Meta's active AI hiring is concentrated in: agents (24%), application (20%), serving infrastructure (16%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Meta is hiring AI talent in: United States (112 roles), United Kingdom (9 roles), France (7 roles), Singapore (6 roles).
Job postings at Meta most frequently mention: Machine Learning, Large Language Models (LLMs), Agentic Systems, Robotics, Generative AI.
In the past 30 days, Meta has posted 66 new AI-related roles. That is a +100% change versus the prior 30 days (33 → 66).
| Title | Stage | AI score |
|---|---|---|
| Lead, Product Content Engineering Meta is seeking a Lead, Product Content Engineering to manage a team focused on evaluating and improving AI content experiences. This role involves developing strategies for LLM evaluation, leading a team of content engineers, driving sprints for LLM evaluations and tooling, and collaborating with cross-functional teams to align AI behaviors with user expectations. The position requires experience with GenAI products, prompt engineering, content evaluation, and working with ranking systems, with a focus on delivering business impact at scale in a dynamic environment. | Eval Gate | 7 |
| Lead, Product Content Engineering This role focuses on driving evaluation efforts for LLM models across product teams, specifically within Meta's Product Content Engineering team. The individual will lead sprints, develop automation strategies for manual evaluation tasks, and partner with Product Managers to align resources. The role involves understanding technical product needs, translating them into actionable directions for cross-functional teams, and contributing to content strategies that improve user experience and content discovery. It requires expertise in GenAI products, prompt engineering, annotation, evaluation metrics, and a strong understanding of recommendation systems and content platforms. |
| Eval GatePost-train |
| 7 |
| Product Content Engineer This role focuses on defining and implementing content quality standards for AI-powered experiences, specifically within Meta's AI Discovery team. The Product Content Engineer will build frameworks, rubrics, and pipelines to evaluate AI outputs, assess model behavior, and collaborate with cross-functional teams to improve AI content experiences, particularly in search and recommendation systems. | Eval Gate | 7 |
