Lead ML Engineer - Recommender Systems

Vamp; California (MO); On-site; USD 138,000 - 184,000; Full time

Job summary

Meta is seeking talented Machine Learning engineers to join teams building products that connect billions globally. The role focuses on leadership in ML, recommendation systems, and scalable software, collaborating across product, design, and operations to deliver high-impact experiences.

You will work on diverse platforms including mobile and web, architecting efficient systems and guiding peers through complex technical challenges.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or equivalent practical experience
• 4+ years of software engineering experience
• 3+ years in ML, recommender systems, or AI
• Experience building ML models at scale
• Experience with C/C++ and Java, or Python, Perl, PHP, or shell scripting
• Experience with Python, JavaScript or Hack
• Experience leading major technical initiatives
• Experience designing or deploying recommender systems
• Hands-on with large language models (LLMs) in production

Responsibilities

• Collaborate with cross-functional teams to build innovative experiences
• Implement custom user interfaces using modern programming techniques
• Develop reusable software components interfacing with back-end platforms
• Analyze and optimize code for quality, efficiency and performance
• Lead complex technical or product efforts and provide guidance
• Architect efficient and scalable systems for complex applications
• Identify and resolve performance and scalability issues
• Work across multiple languages and technologies
• Own components, features, or systems with end-to-end ownership

Skills

Machine Learning

Recommendation Systems

C/C++

Java

Python

LLMs

Education

Bachelor's degree in Computer Science/Engineering or equivalent

Tools

C/C++

Java

Job description

Meta is seeking talented Machine Learning engineers to join teams building products that connect billions globally. The role focuses on leadership in ML, recommendation systems, and scalable software, collaborating across product, design, and operations to deliver high-impact experiences.

You will work on diverse platforms including mobile and web, architecting efficient systems and guiding peers through complex technical challenges.