Software Engineer, Machine Learning

Meta is seeking talented engineers to join our teams in building cutting-edge products that connect 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. If you're interested in joining a team of engineers and researchers to work on exciting projects that have significant impact, we encourage you to apply.

Responsibilities

Collaborate with cross-functional teams (product, design, operations, infrastructure) to build innovative application experiences Implement custom user interfaces using latest programming techniques and technologies Analyze and optimize code for quality, efficiency, and performance, and provide feedback to peers during code reviews Set direction and goals for teams, lead major initiatives, provide technical guidance and mentorship to peers, and help onboard new team members Architect efficient and scalable systems that drive complex applications Identify and resolve performance and scalability issues, and drive large efforts to reduce technical debt Work on a variety of coding languages and technologies Establish ownership of components, features, or systems with expert end-to-end understanding

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 8+ years of programming experience in a relevant language OR 4+ years experience with a PhD Demonstrated experience driving change within an organization and leading complex technical projects Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions Masters degree or PhD in Computer Science or a related technical field Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Grasp of data structures and algorithms, including graph theory and optimization techniques Knowledge of NLP techniques, including text preprocessing, tokenization, and sentiment analysis Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Understanding of information retrieval concepts, such as indexing, querying, and ranking Experience with frameworks like TensorFlow, PyTorch, or Scikit-learn