Software Engineer, Machine Learning
Description
Meta is seeking talented engineers to join our Central Integrity team which exists to keep billions of people safe on Meta's platforms. We design and deploy systems that detect and disrupt harm at an unprecedented global scale, making this one of the largest deployments of AI for positive real-world impact anywhere in the industry. Our work safeguards critical areas including child and youth safety, fraud and scams, identity and authenticity and more while actively building defenses against novel frontier threats, such as autonomous AI agents and automated risk vectors. This represents some of the most technically demanding and high-stakes engineering and product at Meta, driven by a deeply mission-focused team. You'll combine strong engineering fundamentals with cutting-edge AI to build effective, adaptable solutions that stay ahead of evolving integrity and safety risks. If you are driven by hard technical challenges and want your work to deliver immediate, real-world impact, this is where you belong.
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
Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Demonstrated experience driving change within an organization and leading complex technical projects Programming experience in a relevant language Knowledge of NLP techniques, including text preprocessing, tokenization, and sentiment analysis Experience with frameworks like TensorFlow, PyTorch, or Scikit-learn 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 Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Masters degree or PhD in Computer Science or a related technical field Understanding of information retrieval concepts, such as indexing, querying, and ranking Demonstrated experience with data structures and algorithms, including graph theory and optimization techniques