Research Engineer role focused on building Meta's User Intelligence Engine for the Recommendation System, integrating Generative AI/LLMs with ranking expertise to deliver personalized experiences. Responsibilities include developing large-scale model architectures, leveraging transfer learning, optimizing training scalability, applying sequence learning, designing generative modeling for data augmentation, and deploying ML pipelines. Requires a Bachelor's degree in a relevant field, ML/deep learning/recommender systems experience, Python/PyTorch proficiency, and exposure to large-scale software patterns. Preferred qualifications include a Master's/PhD, publication record, generative AI/LLM/RecSys experience, and experience with large-scale ML model development.

Lead QA Engineering for AI-powered products at Meta, focusing on testing text, image, and voice models. Develop and execute test strategies, including prompt engineering, scenario-based, and adversarial testing, ensuring robustness, reliability, and ethical standards. Collaborate with AI/ML teams, leverage AI tools for QA workflows, and drive quality for billions of users.

Product Manager to drive AI transformation at scale, evaluating AI solutions, championing AI-native strategies, and scaling AI best practices. Responsibilities include defining product vision, driving development with cross-functional teams, orchestrating execution with AI automation, and defining/running evaluations for AI-powered experiences. Requires experience building AI-native products and integrating AI tools to optimize workflows, with a focus on responsible AI practices and ongoing AI skill development.

Research Engineer focused on advancing AI, ML, and RecSys technologies for personalized ads, aiming to maximize user utility and advertiser value. The role involves developing and implementing large-scale model architectures, sequence learning techniques, and generative modeling solutions for data augmentation, with a focus on integrating these into production systems that drive significant revenue.

Technical Program Manager to lead cross-functional programs for FAIR, focusing on compute infrastructure, data management, and generative AI projects. The role involves partnering with researchers and engineers to deliver scalable solutions, guide technical strategy, and ensure the productionization of generative models, while adhering to ethical AI practices and evaluating model performance.

Director of Data Engineering at Meta, focusing on measuring the impact of AI for Work (AI4W) across the enterprise. This 0->1 role involves building measurement frameworks, data pipelines, and instrumentation to track agent telemetry and outcome metrics. The goal is to quantify the ROI of AI tools, validate claimed impact, and shape the strategy for AI-augmented productivity. The role requires operating across diverse AI use cases and influencing stakeholders to evolve operating models for the AI era.

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.

Software Engineer, Machine Learning at Meta focused on developing and testing operating systems-level software, compilers, and network distribution software for massive social data and prediction problems. The role involves applying deep learning, data regression, and rules-based models to classification and optimization tasks such as fraud detection, ad ranking, recommendation systems, and spam detection, with a focus on building highly scalable and efficient systems.

Machine Learning Engineer at Meta focused on designing, implementing, and productionizing ML models for ad ranking, targeting, and conversion optimization. This role involves leading experiments, building scalable ML pipelines, and collaborating with cross-functional teams. Requires a Master's degree and 3 years of experience in ML, deep learning, distributed computing, and Python/C++.

Director, Data Science - AI for Work (AI4W) Ecosystem at Meta. This role is a founding senior IC on a new analytics team focused on integrating AI into Meta's products and processes. The role involves shaping product development, measuring impact, strategizing investments, and guiding teams with data-driven insights. Responsibilities include collaborating with cross-functional partners, contributing to technical vision, building and improving AI development/experimentation/measurement systems, and leading data scientists and managers. Requires experience in predictive modeling, ML, experimentation, ethical AI practices, and AI skill development like prompt engineering and agent orchestration.

Software Engineer, Machine Learning at Meta focused on developing and testing operating systems-level software, compilers, and network distribution software for massive social data and prediction problems. The role involves working on classification and optimization problems using deep learning, data regression, and rule-based models to build highly scalable systems and algorithms.

Product Manager to lead AI-native product development at scale, defining AI strategies, overseeing product vision, roadmap, and execution. This role requires critically evaluating AI's role, translating capabilities into product visions, developing comprehensive AI strategies with evals and data strategies, and scaling AI best practices across product teams. The PM will orchestrate execution using AI automation and human oversight, foster experimentation, and mentor others on AI-native practices.

Meta is seeking a Sr. Data Scientist to work with large datasets, solve complex problems using analytical and statistical approaches, and partner with Product and Engineering teams. The role involves informing product decisions, working with data infrastructure (Hadoop, Hive, MySQL), authoring pipelines (SQL, Python ETL), guiding experimentation, and developing machine learning models including label design and evaluation. The scientist will leverage Python and R to make strategic business decisions, apply causal inference, design/evaluate experiments, monitor metrics, build dashboards, and develop models of user behavior. This includes influencing product teams through presentations, communicating results, and spreading best practices. The role requires applying predictive modeling, machine learning, and experimentation/causal inference methods regularly.

Machine Learning Engineer at Meta focused on developing and deploying scalable ML models for consumer-facing problems like fraud detection, ad/feed/search ranking, and spam detection. The role involves research, design, development, testing, and production deployment of these models, working with data pipelines, and collaborating with cross-functional teams.

Meta is looking for a principal engineer to lead teams in building and improving AI-powered products that connect billions of people globally. The role involves driving technical direction, developing roadmaps, and mentoring stakeholders, with a focus on integrating AI tools and adhering to responsible AI practices.

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.

Meta is seeking an experienced Voice Producer to lead AI voice and production projects, combining voice production expertise with organizational and operational leadership. The role involves managing all phases of voice production, ensuring collaboration, and driving the success of voice and audio experiences. It also includes deploying and scaling AI-enabled workflows to improve efficiency and predictability.

Data Scientist role at Meta focused on product development, leveraging quantitative analysis, data mining, and machine learning to understand user interactions and inform product decisions. The role involves forecasting business trends and partnering with product and engineering teams.

Product Manager at Meta focused on AI-based applications and generative AI products. Responsibilities include driving product strategy, defining requirements, collaborating with ML teams, and managing the product lifecycle. Requires experience in product management, AI product strategy, technical architecture, and data analysis.

Data Scientist at Meta focused on understanding user behavior and powering production systems with models. Responsibilities include quantitative analysis, data mining, partnering with product/engineering, defining metrics, building dashboards, and automating pipelines using SQL and Python. Requires a Master's degree and coursework/experience in machine learning, SQL, Python, and statistical analysis.