Software Engineer, Machine Learning

Meta is seeking a Machine Learning Software Engineer to join their team in Menlo Park, CA. This role offers an exciting opportunity to work at the intersection of machine learning and large-scale social technology. As a Machine Learning Engineer at Meta, you'll be responsible for developing cutting-edge solutions for massive social data and prediction problems.

The position involves working on a diverse range of challenges including ranking systems, recommendation engines, and optimization problems. You'll be developing highly scalable systems and algorithms leveraging deep learning, data regression, and rules-based models. The role requires expertise in adapting machine learning methods for modern parallel environments and working with state-of-the-art deep learning techniques.

Meta offers a competitive compensation package ranging from $185,644 to $200,200 annually, plus bonus and equity opportunities. The company provides comprehensive benefits and the chance to work on technologies that impact billions of users globally. You'll be part of Meta's mission to build the next evolution in social technology, moving beyond traditional social media into immersive experiences like AR and VR.

The ideal candidate will have a Master's degree in Computer Science or related field, with strong expertise in machine learning frameworks, distributed systems, and programming languages like Python, Java, and C++. You'll need experience with big data tools like Hadoop/Spark and deep learning frameworks such as PyTorch or Tensorflow. This role offers the opportunity to work on challenging problems at scale while contributing to the future of social technology.

Working at Meta means joining a company at the forefront of technological innovation, with a strong focus on machine learning and AI applications. You'll collaborate with talented engineers and researchers, have access to vast computational resources, and work on problems that affect users worldwide. The company's commitment to pushing technological boundaries and its massive user base provide unique opportunities for professional growth and impact.