Software Engineer (Junior & New Grad ML Infrastructure)

Join our team as a Machine Learning Infrastructure Engineer, where you'll help build the backbone that trains, serves, and monitors the models behind our Ads and Recommendations products. You'll work across the ML lifecycle, from design to rollout to post-launch learnings, and have the opportunity for real autonomy with support. This is a great opportunity for someone who enjoys building reliable systems and has a passion for machine learning.

• 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, enhancing their functionality and reliability, and ensuring they meet the needs of the ML teams.
• We’re looking for someone who can take real ownership, finish what’s started, and raise the bar on stability and developer experience
• You like building reliable systems that make ML teams move faster—and you enjoy turning complexity into simple, durable solutions
• Familiarity with software development processes, including version control, bug tracking, and design documentation
• Basic knowledge of Applied Machine Learning and experience with major Deep Learning frameworks, such as PyTorch and TensorFlow
• Bachelor’s degree in Computer Science, Engineering, or a related field with 2+ years of relevant work experience; or a Master’s/PhD in a related discipline
• Proficient in Python, with a strong understanding of object-oriented languages such as C++ or Java
• Familiarity with cloud services such as AWS, GCP, Azure, and others
• A systematic, data-driven problem-solving approach combined with strong communication skills
• Contributions to open-source machine learning or infrastructure tools