Software Engineer, Machine Learning - AI Solutions and Automation + Support

Meta•Menlo Park, CA

11d•$183,997 - $257,000

About The Position

Meta is seeking experienced engineers to join AI Solutions and Automation + Support (ASA+S), applying state-of-the-art AI and autonomous agents to products and support experiences used by billions of people. The team builds agents that resolve real problems for users, creators, and businesses, along with the platforms, evaluation systems, and model infrastructure needed to deploy those agents safely and at scale. This role focuses on applied AI in production: building and optimizing LLM and agentic systems, designing trustworthy data and evaluation foundations, and taking emerging techniques from prototype to production. The work is intended to create reusable platforms that other teams can build on and deliver novel agent capabilities to real users.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
Eight or more years of programming experience in a relevant language, or four or more years of experience with a PhD.
Programming experience in a relevant language.
Demonstrated experience driving organizational change and leading complex technical projects.
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.
Demonstrated grasp of data structures and algorithms, including graph theory and optimization techniques.
Understanding of information retrieval concepts such as indexing, querying, and ranking.
Experience implementing responsible and ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews.
Experience with frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Knowledge of NLP techniques, including text preprocessing, tokenization, and sentiment analysis.
Experience with inference infrastructure, model evaluations, agent runtime, or synthetic data generation.
Ability to integrate AI tools to optimize or redesign workflows and drive measurable impact, such as efficiency gains or quality improvements.
Ongoing AI skill development, such as prompt or context engineering and agent orchestration, and keeping 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, scalable systems for complex applications.
Identify and resolve performance and scalability issues, and lead efforts to reduce technical debt.
Work with a variety of programming languages and technologies.
Own components, features, or systems with expert end-to-end understanding.