Software Engineer, Machine Learning

Meta is seeking talented engineers to join our teams in building cutting-edge products that connect billions of people around the world. As a member of our team, you will have the opportunity to work on complex technical problems, build new features, and improve existing products across various platforms, including mobile devices and web applications. Our teams are constantly pushing the boundaries of user experience, and we’re looking for passionate individuals who can help us advance the way people connect globally. If you’re interested in joining a world-class team of industry veterans and working on exciting projects that have a significant impact, we encourage you to apply.

1. Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

2. Track record of setting technical direction for a team, driving consensus and successful cross-functional partnerships

3. 6+ years of programming experience in a relevant language or 3+ years of experience + PhD

4. Experience building maintainable and testable code bases, including API design and unit testing techniques

Preferred Qualifications:

Preferred Qualifications:

1. Experience building and shipping high quality work and achieving high reliability

2. Experience improving quality through thoughtful code reviews, appropriate testing, proper rollout, monitoring, and proactive changes

3. Experience with developing machine learning models at scale from inception to business impact

4. Exposure to architectural patterns of large scale software applications

5. Experience with scripting languages such as PyTorch, TensorFlow, Python, JavaScript or Hack

6. 2+ years of experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or a related technical field

7. Knowledge developing and debugging in C/C++ and Java

8. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

9. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

10. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies