Software Engineer, Machine Learning RecSys

Meta is seeking talented Machine Learning engineers to join our teams in building cutting-edge products, with the mission of connecting billions of people around the world. As a member of our team, you will have the opportunity to work on complex technical problems, build new features, and improve existing products across various platforms, including mobile devices and web applications. Our teams are constantly pushing the boundaries of user experience, and we're looking for passionate individuals who can help us advance the way people connect globally.

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 2+ years of programming experience in a relevant programming language
• 1+ years of hands-on experience in one or more of the following areas: machine learning, recommendation systems, llms or artificial intelligence
• Experience with scripting languages such as Python, Java script or Hack
• Experience with developing machine learning models at scale from inception to business impact
• Knowledge developing and debugging in C/C++ and Java, or experience with scripting languages such as Python, Perl, PHP, and/or shell scripts
• Track record of setting technical direction for a team, driving consensus and successful cross-functional partnerships
• Proven experience designing, building, or deploying recommendation systems (e.g., collaborative filtering, content-based, hybrid approaches, personalization at scale)
• Experience building and shipping high quality work and achieving high reliability
• Experience improving quality through thoughtful code reviews, appropriate testing, proper rollout, monitoring, and proactive changes
• Masters degree or PhD in Computer Science or another ML-related field
• Exposure to architectural patterns of large scale software applications
• Experience with scripting languages such as Pytorch and Tensor Flow
• Publications in top-tier conferences/journals, patents, or open-source contributions in the recommendations or LLM space
• Hands-on experience working with large language models (LLMs), such as BERT, GPT, or similar architectures, including fine-tuning, integration, or application in production environments
• 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