Machine Learning Engineer

Meta, formerly Facebook, is seeking a Machine Learning Engineer to join their team in Menlo Park. This role sits at the intersection of machine learning and large-scale engineering, focusing on developing sophisticated ML systems that power Meta's suite of social technologies.

The position offers an opportunity to work on massive-scale machine learning problems, including ranking, classification, recommendation systems, and optimization challenges across Meta's family of apps and services. You'll be developing solutions that leverage deep learning, data regression, and rules-based models to solve complex technical challenges.

As a Machine Learning Engineer, you'll be responsible for researching, designing, and implementing operating systems-level software, compilers, and network distribution software. The role requires expertise in machine learning frameworks like PyTorch or TensorFlow, and a strong foundation in probability theory, linear algebra, and calculus.

The ideal candidate will have a Bachelor's degree in Computer Science or related field, with demonstrated experience in machine learning applications. You'll work with cutting-edge technologies and frameworks, including distributed systems, deep neural networks, and big data technologies like Hadoop and Spark.

Meta offers a competitive compensation package including a base salary range of $187,974 to $200,200, plus bonus, equity, and comprehensive benefits. You'll be joining a company at the forefront of technological innovation, particularly in areas like AR/VR and the metaverse.

This role provides an excellent opportunity to work on challenging problems at scale, collaborate with world-class engineers and researchers, and make a significant impact on products used by billions of people worldwide. The position offers both technical depth and the chance to work on projects that shape the future of social technology and human connection.

Meta provides a supportive and inclusive work environment, with a strong commitment to diversity and equal opportunity employment. The company offers various resources and support systems to help employees grow and succeed in their careers while maintaining work-life balance.