Software Engineer, Machine Learning

Meta is seeking a Software Engineer specializing in Machine Learning to join their team in Menlo Park. This role combines advanced machine learning expertise with software engineering to solve complex challenges in social technology. The position involves working on massive-scale data problems, developing and implementing machine learning solutions for various applications including ranking, classification, and recommendation systems.

The ideal candidate will have a strong foundation in both software engineering and machine learning, with a Master's degree in a relevant field. You'll be working with cutting-edge technologies and frameworks like PyTorch, TensorFlow, and distributed computing systems to build solutions that impact billions of users worldwide.

At Meta, you'll be part of a team that's pushing the boundaries of social technology and moving beyond traditional social media into immersive experiences like AR and VR. The role offers competitive compensation including base salary ranging from $258,524 to $290,180, plus bonus, equity, and comprehensive benefits.

Key responsibilities include developing scalable machine learning systems, optimizing algorithms for massive data sets, and working with distributed computing environments. You'll collaborate with cross-functional teams to implement solutions for various use cases from fraud detection to content recommendation.

Meta offers a dynamic work environment where you'll be at the forefront of technological innovation, working on problems that affect billions of users. The company's commitment to pushing technological boundaries and its massive scale provide unique opportunities for professional growth and impact.

The position requires expertise in multiple programming languages, machine learning frameworks, and distributed systems. You'll need to demonstrate strong problem-solving abilities and experience with large-scale systems. Meta's collaborative culture and extensive resources will support your work in developing next-generation solutions for social technology challenges.