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 121 active AI roles, up 55% versus the prior 4 weeks. Primary focus: Ship · Research.
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 |
|---|---|---|
| Partner Engineer, Generative AI Integration and Distribution Partner Engineer focused on enabling strategic partners to integrate and distribute Meta's generative AI products and platforms. This role involves technical leadership, solution design, shipping production code, and building strong partner relationships within the AI developer ecosystem. | Ship | 8 |
| Research Engineer Robotics (Systems) Meta's Reality Labs Research is seeking a Staff Research Engineer to lead the end-to-end technical architecture for dexterous robotic manipulation systems. This role involves integrating perception, planning, and control, deploying learned control policies (including imitation learning and reinforcement learning), and building infrastructure for data capture and processing. The engineer will optimize system performance, set technical direction, and mentor other engineers, bridging the gap between research and production in robotics. |
| ShipData |
| 8 |
| Partner Engineer, Generative AI Partner Engineer focused on Generative AI, specifically working with strategic partners and cloud providers to build and launch AI product services and experiences using Meta's Llama LLMs. The role involves taking LLMs from research to production, developing technical accelerators, evangelizing Meta's AI, and optimizing models for performance and scalability. Requires strong software development skills, experience with deep learning frameworks, and cloud solutions. | ShipPost-train | 8 |
| Computer Vision Engineer, Reality Labs Computer Vision Engineer for Meta's Reality Labs, focusing on AR/VR products. Responsibilities include researching and developing software, computer vision, and machine learning techniques for real-time image processing, 3D graphics, SLAM, scene reconstruction, machine perception, and human interaction. The role involves designing calibration algorithms, collaborating with cross-functional teams, and contributing to engineering best practices. Requires a Bachelor's degree in a relevant field, 3+ years of experience in Computer Vision/Perception for Robotics, C++ engineering, and expertise in areas like Camera Calibration, State Estimation, or 3D Reconstruction. An MS or PhD and a publication track record at top conferences are preferred. | Ship | 7 |
| AI Transformation Lead, Hardware Engineering This role leads the AI transformation within hardware engineering for consumer electronics (wearables, AR/VR). It involves defining roadmaps, deploying ML/GenAI into design, simulation, and manufacturing workflows, and bridging the gap between AI research and practical hardware applications. The focus is on accelerating hardware development cycles and improving engineering outcomes through AI integration. | Ship | 7 |
| Software Engineer, Machine Learning RecSys Meta is looking for a Machine Learning Engineer to build and improve cutting-edge recommendation systems and AI-powered products for billions of users. The role involves collaborating with cross-functional teams, implementing ML models at scale, and driving product impact. | ShipPost-train | 7 |
| Robotics Verification & Validation Engineer Meta is seeking a Robotics Verification & Validation Engineer for their humanoid robotics team. The role focuses on ensuring the reliability, safety, and performance of the robot platform through end-to-end V&V of hardware, software, firmware, and AI components. Responsibilities include developing V&V plans, creating test environments, leading root cause analysis, and ensuring compliance with safety standards. The role requires experience with safety-critical systems, functional safety standards, and validating systems with integrated AI/ML, particularly in perception and decision-making. | ShipAgent | 7 |
| Robotics Manipulation Engineer Meta is seeking a Robotics Engineer to join their Infra Robotics team, focusing on integrating robotics and automation into data center operations. The role involves solution architecture, system integration, verification, and product release, with a strong emphasis on hands-on experience with industrial robotics, automation software development, and ML algorithms for robot interaction. The engineer will collaborate with cross-functional teams to improve serviceability, repair efficiency, and reliability. | Ship | 7 |
| Software Engineer (Technical Leadership) Software Engineer with technical leadership responsibilities focused on applying machine learning to large-scale consumer prediction problems like fraud detection, recommendation systems, and classification. The role involves driving technical direction, developing scalable ML models, and shipping products to millions of users. | Ship | 7 |