Software Engineer, Infrastructure - Ads Infra and Ranking

Meta; Bellevue (WA); On-site; USD 180,000 - 240,000; Full time

Job summary

Meta's Ads organization builds the systems that help businesses of every size reach the people most likely to care about what they offer. At our core, we’re builders who care about shipping real value.

Within Ads, the Infra and Ranking organization owns the technical foundation for ranking models and serving platforms at Meta's scale. As a Software Engineer, Infrastructure, you will lead complex systems engineering projects, design and improve distributed services with a focus on reliability,

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, 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 experience with a PhD
• Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions

Responsibilities

• Design, build, and improve distributed services and platform capabilities supporting Ads data, training, experimentation, real-time serving, or compute capacity.
• Use system data and analysis to diagnose reliability, latency, throughput, and resource-efficiency issues and compare technical solutions.
• Lead complex systems projects from design through production rollout, coordinating dependencies across infrastructure and ML engineering partners.
• Develop maintainable software, interfaces, and operational tooling that improve platform usability and reduce engineering toil.
• Improve production quality through testing, code review, observability, safe rollout, and incident response.
• Communicate technical trade-offs, balance platform stability with Ads innovation, and mentor engineers to raise the team's engineering standards.

Skills

Distributed systems

Mentoring

System design

Data analysis

Project leadership

Problem solving

Education

Bachelor's degree in Computer Science / Engineering

PhD in Computer Science (optional with 4+ years experience)

Tools

C/C++

Java

Python

JavaScript

Linux

Job description

Meta's Ads organization builds the systems that help businesses of every size reach the people most likely to care about what they offer. At our core, we're builders who care about shipping real value. Within Ads, the Infra and Ranking organization owns the technical foundation that makes this work at Meta's scale: the ranking models that decide which ad is right for each moment; the retrieval and serving platforms that evaluate enormous candidate sets in milliseconds; and the underlying data, training, and inference infrastructure. All of this is done while maximizing compute efficiency, ensuring reliability and privacy, and using AI to speed up development.

As a Software Engineer, Infrastructure in Ads Infra and Ranking, you will lead complex systems engineering projects that strengthen the platforms behind Ads retrieval and ranking: data and features, training, evaluation and experimentation, and serving. You will design and improve distributed services with a focus on reliability, performance, privacy, and resource efficiency, working with infrastructure and ML partners to enable dependable production systems and faster iteration.

Responsibilities

• Design, build, and improve distributed services and platform capabilities supporting Ads data, training, experimentation, real-time serving, or compute capacity.
• Use system data and analysis to diagnose reliability, latency, throughput, and resource-efficiency issues and compare technical solutions.
• Lead complex systems projects from design through production rollout, coordinating dependencies across infrastructure and ML engineering partners.
• Develop maintainable software, interfaces, and operational tooling that improve platform usability and reduce engineering toil.
• Improve production quality through testing, code review, observability, safe rollout, and incident response.
• Communicate technical trade-offs, balance platform stability with Ads innovation, and mentor engineers to raise the team's engineering standards.

Minimum qualifications

• Bachelor's degree in Computer Science, Computer Engineering, 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 experience with a PhD
• Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions

Preferred qualifications

• 6+ years relevant experience building large-scale infrastructure applications or similar experience
• Experience building distributed services or data platforms behind advertising, business-facing, or analogous large-scale products
• Experience designing reliable service interfaces and diagnosing correctness, performance, or data-quality issues across product integrations
• Experience in programming languages such as C, C++, or Java, and scripting languages such as Python, Javascript, or Hack
• Experience improving quality through code review, testing, controlled rollout, monitoring, and proactive changes
• Demonstrated ability to integrate AI tools into infrastructure engineering and operational workflows and drive measurable efficiency or quality improvements
• Experience applying responsible AI practices, including risk assessment and quality and accuracy reviews, when developing or using AI-assisted product infrastructure tooling
• Demonstrated ongoing AI skill development, including prompt/context engineering or agent orchestration, and evaluation of emerging technologies for infrastructure engineering use
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies