We’re looking for applied scientists with substantial industry experience to join the Central Applied Science team. Central Applied Science is home to experts from many scientific fields, partnering across the company to deliver engineering systems that bring research and innovation to fundamentally contribute to Meta's success. You will be empowered to leverage your expertise and drive impact across a range of products, infrastructure and company operations. Individuals in this role are expected to perform well in a research engineering capacity and hold publications within research areas including artificial intelligence, machine learning, statistics, operations research, causal inference and experimentation. Experience building data-driven products and forming research frameworks to solve challenging, real-world problems.
Responsibilities
Work with vast amounts of data, generate research questions that push the state-of-the-art, and build data-driven products which impact the business Develop novel quantitative methods on top of Meta's unparalleled data infrastructure Work towards long-term ambitious research goals, while identifying intermediate milestones Communicate best practices in quantitative analysis to partners Work both independently and collaboratively with other scientists, engineers, and product managers to accomplish complex tasks that deliver demonstrable value to Meta's community of over 3.8 billion users Actively identify new opportunities for scientific tooling and systems to yield outsized impact, in line with Central Applied Science's role and mission within Meta
Qualifications
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience PhD in computer science, statistics, operations research or a related field 4+ years of industry experience in an applied R&D capacity or similar function Publications in Machine Learning, AI, computer science, statistics, data science, or related technical fields Experience analyzing datasets using languages such as Python Experience using machine learning and deep learning frameworks, such as PyTorch, TensorFlow or scikit-learn Experience developing algorithms in languages such as Python, C, C++ or Java Experience analyzing large datasets using tools such as Presto, Hive or Spark Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment Track record of building end-to-end systems which bring science and engineering to solve critical business problems Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Engagement with leaders to drive decision-making based on a thorough understanding of science and business constraints