Sourceo Hiring! Full Time Software Engineer, Recommendation Systems in - Ricebowl

Meta is seeking a Software Engineer to join our Recommendation Systems team, where you will build and advance the machine learning infrastructure and ranking systems that power personalized experiences across Meta's family of apps — including Facebook Feed, Reels, Marketplace, and more. In this role, you will design and optimize large-scale recommendation and retrieval systems that serve billions of users, working at the intersection of machine learning, data engineering, and product impact. You will collaborate closely with machine learning engineers, product managers, and data scientists to define the technical direction of recommendation pipelines and deliver measurable improvements to user engagement and relevance.

Responsibilities

• Design, build, and optimize large-scale recommendation and ranking systems that personalize content across Meta's core products
• Develop and improve retrieval, candidate generation, and multi-stage ranking pipelines to enhance relevance and user engagement
• Instrument recommendation systems with telemetry, dashboards, and alerting to maintain reliability and surface regressions early
• Lead the technical design of recommendation infrastructure components, evaluating trade-offs across latency, throughput, and model quality
• Run and analyze A/B experiments to validate ranking and retrieval hypotheses, translating results into data-informed product decisions
• Identify and resolve performance bottlenecks in recommendation serving stacks using profiling and instrumentation
• Drive engineering excellence by establishing coding standards, improving test coverage, and leading code reviews for recommendation system components
• Collaborate with machine learning engineers and data scientists to integrate new model architectures into production ranking pipelines
• Mentor other engineers on recommendation systems best practices, system design, and experiment methodology
• Proactively identify opportunities to reduce technical debt and improve the scalability and maintainability of recommendation infrastructure

Minimum Qualifications

• 6+ years of software engineering experience, with a focus on building and scaling recommendation, ranking, or retrieval systems
• Experience designing and implementing large-scale distributed systems with low-latency serving requirements
• Experience with machine learning model integration in production environments, including feature engineering, model serving, and pipeline development
• Experience running A/B experiments and using experimental outcomes to drive product and engineering decisions
• Experience with performance profiling, debugging complex production issues, and establishing reliability practices such as service level objectives and monitoring

Preferred Qualifications

• Experience with real-time feature pipelines and online learning systems for recommendation use cases
• Track record of driving cross-functional technical initiatives that delivered measurable improvements to recommendation quality or system efficiency
• Experience with multi-stage ranking architectures, including candidate retrieval, scoring, and re-ranking at internet scale
• Proficiency in machine learning frameworks such as PyTorch or TensorFlow, and experience with embedding-based retrieval or approximate nearest neighbor search

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.