Software Engineer, Machine Learning

Meta•Menlo Park, CA

3d•$183,997 - $257,000

About The Position

Meta is hiring a Software Engineer, Machine Learning for its Central Integrity team, which develops systems to detect and disrupt harm across Meta’s platforms at global scale. The team safeguards areas including child and youth safety, fraud and scams, identity and authenticity, and emerging threats such as autonomous AI agents and automated risk vectors. The role combines engineering fundamentals with AI to build effective, adaptable solutions for evolving integrity and safety risks. The engineer collaborates across product, design, operations, and infrastructure; builds application experiences and custom user interfaces; and helps architect, scale, and optimize complex systems. The position also involves technical leadership, mentoring, code review, resolving performance and scalability issues, reducing technical debt, and owning components or systems end to end.

Requirements

Demonstrated experience driving organizational change and leading complex technical projects.
Bachelor’s degree in Computer Science, Computer Engineering, or a relevant technical field, or equivalent practical experience.
8+ years of programming experience in a relevant language, or 4+ years of experience with a PhD.
Experience using data and analysis to explain technical problems and provide detailed feedback and solutions.

Nice To Haves

Master’s degree or PhD in Computer Science or a related technical field.
Experience with frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Understanding of information retrieval concepts, including indexing, querying, and ranking.
Grasp of data structures and algorithms, including graph theory and optimization techniques.
Knowledge of NLP techniques, including text preprocessing, tokenization, and sentiment analysis.
Ability to integrate AI tools to optimize or redesign workflows and drive measurable impact, such as efficiency gains or quality improvements.
Experience implementing responsible and ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews.
Ongoing AI skill development, such as prompt/context engineering and agent orchestration, and staying current with emerging AI technologies.

Responsibilities

Collaborate with product, design, operations, and infrastructure teams to build innovative application experiences.
Implement custom user interfaces using current 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, and help onboard new team members.
Architect efficient and scalable systems for complex applications.
Identify and resolve performance and scalability issues, and lead efforts to reduce technical debt.
Work with a variety of coding languages and technologies.
Own components, features, or systems and develop expert end-to-end understanding of them.