Software Engineer (ML Infrastructure)

Join our team as a Machine Learning Infrastructure Engineer, where you'll play a crucial role in building the backbone that trains, serves, and monitors the models behind our Ads and Recommendations products. You'll work across the entire ML lifecycle, from training to model serving, and have the opportunity to make a significant impact in production. This position offers a high level of ownership, autonomy, and growth potential, as well as a range of benefits including work from home opportunities, paid time off, and health care for you and your family.

• Design and develop machine learning infrastructure, including systems for offline and online model training, model pipeline health monitoring, model serving, feature authoring, and feature serving.
• Collaborate with ML engineers to build robust model pipelines utilizing the ML infrastructure, and proactively address ML infrastructure issues that may impact production.
• Take ownership of core components of the ML infrastructure, from design to rollout to post-launch learnings, and lead cross-team projects from design through stable rollout.
• If you like building reliable systems that make ML teams move faster—and you enjoy turning complexity into simple, durable solutions—we’d love to talk
• We’re looking for someone who can take real ownership, finish what’s started, and raise the bar on stability and developer experience
• Proven track record in building and maintaining large-scale distributed backend systems
• Proficient in Python, with a strong understanding of object-oriented languages such as C++ or Java
• Strong problem solving skills with good teamwork and communication skills
• Education: Bachelor's degree in a related field with 5+ years of relevant experience, or MS/PhD in a related field with 3+ years of relevant experience
• Experience delivering production systems that support ML use cases (training or serving)
• Experience leading cross-team projects from design through stable rollout
• Experience iterating on ML models and shipping them to production