Job Description

Meta is seeking a Software Engineer with deep AI specialization to help build and scale the artificial intelligence systems that power Meta's family of products and platforms. In this role, you will design, develop, and deploy AI-driven solutions — spanning large language models, generative AI, recommendation systems, and intelligent automation — that directly shape how billions of people connect, communicate, and discover content. You will work at the intersection of applied AI research and production engineering, translating cutting-edge techniques into reliable, high-impact systems. If you are passionate about advancing AI capabilities at scale and driving measurable product outcomes, we encourage you to apply.

Responsibilities
Design and implement scalable AI and machine learning systems, including model training pipelines, inference infrastructure, and feature engineering frameworks, to power Meta's core products
* Develop and optimize large-scale AI models — including large language models, generative AI systems, and ranking and recommendation models — from prototype through production deployment
* Leverage AI tools and workflows as a force multiplier to expand technical scope across modeling, data analysis, and operational readiness within a single project lifecycle
* Establish and maintain robust evaluation frameworks, automated testing, and monitoring pipelines to ensure reliability and quality of AI systems in production
* Own the technical design of AI components and systems, evaluating architectural trade-offs to meet well-defined product and business requirements
* Instrument AI systems with telemetry, design experiments to validate model hypotheses, and make data-informed decisions that balance short-term goals with long-term model quality
* Proactively identify performance bottlenecks in model serving and training infrastructure, using profiling and benchmarking to drive latency and throughput improvements
* Collaborate with product managers, data scientists, and research scientists to translate AI research advances into production-ready features with measurable user impact
* Contribute to AI safety, privacy, and integrity practices by incorporating responsible AI principles into system design and partnering with cross-functional teams on safeguards
* Mentor other engineers on AI engineering best practices, advocate for coding and testing standards, and help drive adoption of AI-augmented development workflows across the team

Qualifications
6+ years of software engineering experience, with a focus on building and deploying machine learning or AI systems in production environments
* Experience designing and implementing end-to-end machine learning pipelines, including data preprocessing, model training, evaluation, and serving at scale
* Experience with deep learning frameworks such as PyTorch or TensorFlow, and proficiency in Python for AI and data engineering workflows
* Experience applying experimentation methodologies — including A/B testing and metric design — to evaluate AI model performance and drive product decisions
* Experience building maintainable, well-tested codebases for AI systems, including unit testing, integration testing, and monitoring for model quality and reliability Experience with large language models, generative AI systems, or retrieval-augmented generation architectures in production settings
* Experience optimizing model inference for latency and throughput, including quantization, distillation, or hardware-aware optimization techniques
* Familiarity with distributed training frameworks and large-scale data processing systems used in AI model development
* Track record of driving AI system improvements through systematic debugging, root cause analysis, and cross-functional incident resolution