Software Engineer, Machine Learning

Meta is hiring a Software Engineer, Machine Learning to build and improve products that connect people. The role focuses on developing application experiences, architecting scalable systems, optimizing performance, and providing technical leadership across teams.

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

Requirements:

• Demonstrated experience driving change within an organization and leading complex technical projects
• 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
• 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
• Experience with frameworks like TensorFlow, PyTorch, or Scikit-learn
• Understanding of information retrieval concepts, such as indexing, querying, and ranking
• Demonstrated grasp of data structures and algorithms, including graph theory and optimization techniques
• Knowledge of NLP techniques, including text preprocessing, tokenization, and sentiment analysis
• 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