Currently tracking 121 active AI roles, up 55% versus the prior 4 weeks. Primary focus: Ship · Research.
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.
Meta currently has 136 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 (23%), 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 (108 roles), United Kingdom (9 roles), France (7 roles), Singapore (6 roles).
Job postings at Meta most frequently mention: Machine Learning, Large Language Models (LLMs), Robotics, Agentic Systems, Generative AI.
In the past 30 days, Meta has posted 67 new AI-related roles. That is a +103% change versus the prior 30 days (33 → 67).
| Title | Stage | AI score |
|---|---|---|
| Research Engineer (Technical Leadership), FAIR Data - Meta Superintelligence Labs Research Engineers at Meta Superintelligence Labs (FAIR) are responsible for building the data foundation for advanced Large Language and Media Models. This includes data curation across pre-training, mid-training, and post-training stages, focusing on challenges at trillion-scale such as organic and synthetic data generation, agent data, and frontier paradigms. The role involves architecting scalable data systems, improving data velocity, and applying expertise in various data modalities and domains. | DataPost-train | 9 |
| AI Research Scientist, Media Data Research - MSL FAIR AI Research Scientist focused on building the data foundation for Meta's advanced Large Language and Media Models. The role involves data curation across pre-training, mid-training, and post-training stages, handling trillion-scale data challenges including organic and synthetic data generation, and contributing to frontier paradigms. Collaboration with cross-functional teams and leading complex technical projects are key. |
| DataPost-train |
| 9 |
| Research Engineer, Text Data Research - MSL FAIR Meta is seeking AI research engineers to build the data foundation for their advanced LLMs. The role involves working with large-scale data across pre-training, mid-training, and post-training stages, focusing on areas like organic data curation, synthetic data generation, agent data, and frontier paradigms. This position is within Meta Superintelligence Labs (MSL) within FAIR, contributing to models like Llama. | DataPost-train | 9 |
| Research Scientist Intern, State Estimation for Dexterous Manipulation (PhD) Research Scientist Intern focused on representation learning for dexterous manipulation in robotics, developing latent space embeddings for object physical state and validating them through experiments. | Data | 8 |
| Visiting Researcher, FAIR (University Grad) Research role focused on defining and establishing foundational data quality standards, task methodologies, and validation frameworks for Computer Use Agent (CUA) data creation, upstream of AI model training. The role involves primary research to set 'gold standard' protocols for data governance and integrity. | Data | 8 |
| Research Scientist Intern, Machine Perception for Input and Interaction (PhD) Research Scientist Intern at Meta's Reality Labs focusing on machine perception for virtual and augmented reality. The role involves developing algorithms for computer vision, machine learning, and sensor fusion for tracking, action recognition, and 3D representation, with a focus on efficient deep learning and real-time applications. | Data | 8 |
| Research Manager Research Manager at Meta focused on product-focused signal processing and sensor development for novel wearable devices and algorithms. The role involves leading a team of research scientists and engineers to create practical, non-invasive wearable devices using machine learning and statistical signal processing to understand user intent and action. Responsibilities include managing teams, collaborating with cross-functional groups (hardware, ML research/engineering), developing methodologies for signal simulation, improving ML models based on sensor limitations, and fostering a learning environment. | Data | 7 |
| Research Scientist, Wearables AI Research Scientist focused on developing novel wearable sensors and algorithms for neuromotor interfaces and AR systems, aiming to reduce latency between user intent and action. Responsibilities include defining sensor requirements, exploring new sensing architectures, building simulation tools, and simulating biophysical signals. | Data | 7 |
| Postdoctoral Researcher, AI Verification, Separation Logic in Lean Research role focused on program verification using AI, specifically embedding Separation Logic into the Lean proof assistant. Responsibilities include conducting original research, automating proofs, developing evaluations, and collaborating on AI for machine learning algorithms and guardrails for AI agents. Requires a PhD, experience with Lean/Separation Logic, and a publication record in AI or Verification/PL venues. | Data | 7 |