Currently tracking 125 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 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 |
|---|---|---|
| Software Engineer, Systems ML Software Engineer specializing in Systems Machine Learning to design and build infrastructure for large-scale AI systems, focusing on training efficiency, model serving, distributed computation, and hardware-software co-design. The role involves translating ML research into production systems and optimizing performance at scale. | ServePost-train | 9 |
| Software Engineer, AI Specialist - Monetization (Technical Leadership) Seeking a distinguished Software Engineer with deep AI specialization to drive transformative technical initiatives across Meta's AI-powered products and platforms. The role involves defining and leading the architectural direction of large-scale AI systems, including foundation models, intelligent ranking and recommendation infrastructure, and applied machine learning pipelines. The engineer will identify and solve complex AI engineering challenges, set technical standards, and leverage AI to unlock new capabilities. This leadership role operates at the intersection of AI research and production-scale engineering, shaping both systems and culture. |
| ServeAgent |
| 9 |
| Software Engineer - AI SysML (Technical Leadership) Meta is looking for an AI Software Engineer to join their R&D teams, focusing on AI Infrastructure and ML Systems. The role involves applying machine learning techniques to optimize intelligent systems, developing custom architectures, defining use cases, and evaluating approaches. The candidate will also drive technical direction, collaborate with leaders, and mentor engineers. Experience in ML systems, AI algorithms, distributed systems, and responsible AI practices is required, with a preference for C/C++ or Python development. | Serve | 8 |
| Software Engineer, SystemML - Scaling / Performance Meta's Network.AI team is seeking Software Engineers to enhance the NCCL software stack, crucial for multi-GPU and multi-node distributed ML training. The role focuses on improving the reliability and performance of large-scale AI/GPU communication for Meta-wide ML products, particularly for GenAI/LLM training and inference. | ServePost-train | 8 |
| Software Engineer, Systems ML Software Engineer focused on AI infrastructure and hardware acceleration for ML systems, optimizing performance and efficiency for Meta's products. Involves C/C++/Python development, distributed systems, and potentially on-device algorithms. Requires technical leadership and experience with ML frameworks and hardware architectures. | Serve | 8 |
| Software Engineer, Systems ML Software Engineer focused on AI Infrastructure, optimizing ML systems and hardware acceleration for Meta's products. Responsibilities include system design, data-driven analysis, cross-team collaboration, and mentoring. Requires expertise in ML infrastructure, C++/Python, distributed systems, and ethical AI practices. | Serve | 8 |
| Technical Program Manager- AI Infrastructure (Ads Ranking) Technical Program Manager (TPM) to lead complex, large-scale programs advancing AI infrastructure and platforms for ad ranking. Focus on optimizing the ML development lifecycle, system reliability, hardware efficiency, and performance at scale. Drive innovation by establishing frameworks for next-generation AI hardware and ML platforms. | ServePost-train | 7 |
| Technical Program Manager, Core Infrastructure Technical Program Manager to lead large-scale projects focused on advancing language model scaling infrastructure. This role involves collaborating across engineering, hardware, data center, research, and product teams to design, build, and scale foundational hardware and software systems supporting AI innovation. Responsibilities include driving the end-to-end integration of AI hardware and core infra, developing frameworks for onboarding, managing cross-functional dependencies, and streamlining workflows. Requires extensive experience in technical program management, understanding of AI hardware/software development, and knowledge of LLMs and distributed systems. | Serve | 7 |
| Machine Learning Hardware Architect - Silicon Machine Learning Hardware Architect role focused on designing and optimizing custom silicon accelerators for AR/VR devices. This role involves leading hardware design from architecture to product, collaborating with researchers and software engineers, and contributing to the development of low-power ML accelerators for high-volume consumer products. | Serve | 7 |
| Design Verification Engineer - Machine Learning Accelerators Meta's Reality Labs is seeking a Design Verification Engineer to work on custom silicon for machine learning accelerators. The role involves developing testing infrastructure to validate new core IP implementations and contributing to the development and optimization of ML algorithms. Responsibilities include defining verification methodologies, implementing test benches, driving verification to closure, and collaborating with cross-functional teams. Requires extensive experience in SystemVerilog/UVM, C/C++, and verification of ML applications and accelerators. | Serve | 7 |
| Software Engineer, Computer Vision - Video AI Software Engineer focused on Computer Vision and Video AI at Meta, developing advanced video solutions for products like Messenger and AR/VR. The role involves researching and developing AI/ML-based compression algorithms to reduce compute footprint and improve user experience, optimizing video codec efficiency, and defining the video optimization roadmap. Requires experience in computer vision, video codecs, and neural compression techniques. | ServeData | 7 |
| Network Engineer, Engineering R&D Environments Meta is seeking a Network Engineer to build and scale network infrastructure for AI and compute lab clusters. This role involves end-to-end network design, deployment, and operations for backend fabrics supporting AI workloads, including high-throughput, low-latency cluster networking. Responsibilities include troubleshooting, supporting hardware/software bring-ups, automation, and collaborating with cross-functional teams. The role requires experience with AI/ML cluster networking and a demonstrated ability to integrate AI tools into workflows. | Serve | 7 |
| Software Engineer Software Engineer role at Meta focused on developing and optimizing large-scale systems for social data and prediction problems. The role involves applying deep learning, data regression, and rule-based models to areas like fraud detection, recommendation systems, and spam detection, with a strong emphasis on adapting ML methods for parallel environments (distributed clusters, GPUs). Requires a Master's degree and 2 years of experience with ML frameworks and distributed systems. | Serve | 7 |
| Software Engineer, Systems Software Engineer focused on building and optimizing AI infrastructure and ML systems, leveraging hardware acceleration techniques to improve Meta's products. The role involves goal setting, data-driven analysis, defining use cases, and mentoring other engineers. | Serve | 7 |