Software Engineer, Machine Learning

Meta is seeking a seasoned Machine Learning Engineer to spearhead transformative changes in their technology landscape. This role represents a unique opportunity to work at the forefront of social technology innovation, where you'll be instrumental in advancing how people connect worldwide.

As a Machine Learning Engineer at Meta, you'll be working alongside world-class engineers and researchers to tackle some of the most challenging social data and prediction problems on the web. The position requires someone who can own the complete ML lifecycle, from conception to implementation, while driving excellence across teams.

The role demands expertise in recommendation systems, classification, and optimization problems, with a focus on developing solutions that can scale to Meta's massive user base. You'll be responsible for adapting ML methods to modern parallel environments, including distributed clusters, multicore SMP, and GPU systems.

Key aspects of the role include technical leadership in setting direction for sizeable teams, developing ML best practices, and handling complex production issues. You'll be working on projects that directly impact billions of users across Meta's family of apps, including Facebook, Instagram, and WhatsApp.

The ideal candidate brings a strong background in software engineering (8+ years, or 4+ with a PhD) and substantial experience in machine learning or related fields. You should be comfortable with various programming languages and frameworks, including Python, Java, and modern ML tools.

This position offers competitive compensation ($85,100 - $251,000/year) plus bonus and equity, along with comprehensive benefits. Based in the San Francisco Bay Area, you'll be at the heart of technological innovation, working on projects that shape the future of digital connection and social technology.

Join Meta to be part of the evolution beyond traditional social media into new frontiers, including augmented and virtual reality. This role offers the chance to work on unprecedented challenges while helping to build the next generation of social technology infrastructure.