Software Engineer, PAR Regulatory Readiness
Meta· Artificial Intelligence
Menlo Park, CA$219k - $301k + equity + bonusFull-timePosted 3w ago
About the role
Meta is seeking a Research Engineer specializing in AI to define and drive the technical direction of AI systems that power products used by billions of people. The role includes architecting large-scale AI infrastructure, foundational model capabilities, and intelligent systems while preparing for upcoming AI regulations, translating advances into reliable production systems, and setting technical standards for AI deployment across Meta.
Responsibilities
- Identify and solve the most complex AI systems challenges across the organization, including problems that span model training, inference optimization, and large-scale deployment pipelines
- Architect extensible, reliable foundations for AI infrastructure that enable multiple teams to build and iterate on machine learning models at scale
- Define technical strategy and roadmap for AI platform capabilities, gaining alignment across engineering, research, and product organizations
- Drive cross-functional execution of multi-year AI initiatives, establishing metrics that connect technical progress to organization-level priorities
- Establish invariants, testing frameworks, and verification standards that prevent entire categories of model correctness and reliability issues in production AI systems
- Identify and resolve systemic performance bottlenecks across the AI stack, from data ingestion and feature engineering through model serving and real-time inference
- Partner with AI research teams to translate theoretical advances in machine learning into production systems that deliver measurable improvements to Meta's products
- Mentor engineers across the organization on AI systems design, debugging techniques, and engineering best practices, serving as a sought-after technical advisor
- Evaluate emerging AI technologies, frameworks, and industry trends to assess their applicability and risk to Meta's AI strategy and competitive position
- Collaborate with legal, policy, and compliance teams to ensure AI systems meet privacy, security, and integrity standards across all deployment contexts
Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- 3+ years of software engineering experience with a focus on AI, machine learning systems, or large-scale distributed systems that support model training and inference
- Experience architecting and owning production AI or machine learning platforms at scale, including end-to-end responsibility for reliability, performance, and evolution of those systems
- Experience defining technical strategy and driving execution across multiple engineering teams, including influencing roadmap priorities and gaining cross-functional alignment
- Experience identifying and resolving systemic issues in AI pipelines, including debugging complex failures that span model behavior, data quality, and infrastructure layers
- Experience establishing engineering standards, architectural patterns, and verification practices that improve the quality and velocity of AI development across an organization
Skills
Required:AI systems designModel trainingInference optimizationDistributed systemsTechnical strategy
Benefits
- Base compensation in United States: $219,000/year to $301,000/year plus bonus and equity plus benefits
- Benefits information available via Meta careers site
Last updated Oct 23, 2026. Interested? Apply on the company site.
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