Software Engineer, Machine Learning - Ads Infra and Ranking

Meta•Menlo Park, CA

2d•$183,997 - $257,000

About The Position

Meta's Ads organization builds systems that help businesses reach people likely to care about their offerings. The Ads Infra and Ranking organization owns the technical foundation for ad ranking, retrieval and serving, as well as the data, training and inference infrastructure behind those systems. Its work focuses on operating at Meta's scale while maximizing compute efficiency and ensuring reliability and privacy. The Software Engineer, Machine Learning will lead complex engineering projects to improve how production ML systems match people with relevant ads. The role translates opportunities to improve model quality into reliable software and measurable results, working across model development, data and serving while balancing relevance with the constraints of large-scale production systems.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
Demonstrated experience driving change within an organization and leading complex technical projects.
8+ years of programming experience in a relevant language, or 4+ years of experience with a PhD.
Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions.

Nice To Haves

Experience developing and deploying ML models for advertising, ranking, retrieval, recommendation or analogous large-scale prediction systems.
Experience applying information retrieval and optimization methods to improve candidate relevance or ranking quality.
Experience with ML frameworks such as PyTorch, TensorFlow or Scikit-learn, including evaluation and integration into production software.
Experience using offline analysis and online experimentation to evaluate model changes and understand quality, latency or efficiency trade-offs.
Experience leading engineering work across model development, data quality and production serving dependencies.
Demonstrated ability to integrate AI tools into ML development, evaluation or debugging workflows with measurable efficiency or quality gains.
Experience applying responsible AI practices, including risk assessment, bias mitigation, and quality and accuracy reviews, to production model development.
Demonstrated ongoing AI skill development, including prompt/context engineering or agent orchestration, and evaluation of emerging technologies for engineering use.
Demonstrated ability to integrate AI tools to optimize or redesign workflows and drive measurable impact, such as efficiency gains or quality improvements.
Experience adhering to and implementing responsible, ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews.
Demonstrated ongoing AI skill development, such as prompt/context engineering or agent orchestration, and staying current with emerging AI technologies.

Responsibilities

Define and deliver ML engineering projects that improve ads ranking or retrieval, from problem framing and model evaluation through production rollout.
Develop models and supporting software, using data and analysis to diagnose quality issues and evaluate alternative approaches.
Partner with infrastructure and ML engineers on the data, feature and serving dependencies needed to turn model improvements into production impact.
Design offline evaluations and online experiments to assess ad relevance, advertiser outcomes and system performance.
Lead technical decisions and cross-functional execution for complex projects, making trade-offs explicit and building maintainable solutions.
Improve production quality through testing, code review, monitoring and iteration across the model lifecycle.
Mentor engineers and help new team members ramp up in relevant codebases and workflows.