Software Engineer, AI/ML

Meta•Redmond, WA

1d•$154,003 - $217,000

About The Position

Meta is seeking an AI/ML Engineer to design, build, and deploy machine learning systems that power widely used products and platforms. The role develops and optimizes AI models and pipelines at scale, using techniques across deep learning, large language models, recommendation systems, and generative AI to address problems across Meta's product ecosystem. It combines applied research with production engineering, translating AI advances into reliable, scalable systems that serve billions of users.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
6+ years of experience designing, training, and deploying machine learning or deep learning models in production environments.
6+ years of experience with ML frameworks such as PyTorch or TensorFlow, and proficiency in Python for model development and data processing.
Experience with large-scale distributed training, model optimization techniques such as quantization, distillation, or pruning, and ML serving infrastructure.
Experience designing and running online experiments (A/B testing) to evaluate model impact on product metrics.
Experience communicating technical decisions and trade-offs in writing to technical and non-technical stakeholders, including through design documents and postmortems.

Nice To Haves

Track record of driving cross-team technical initiatives that improved ML platform capabilities or established new modeling standards across an organization.
Experience with large language models, generative AI systems, or foundation model fine-tuning and alignment techniques.
Experience building recommendation or ranking systems at internet scale, including feature engineering, retrieval, and scoring pipelines.
Experience developing ML observability tooling, including dashboards, alerting, and automated anomaly detection for production model health.

Responsibilities

Design, develop, and deploy large-scale machine learning models and AI pipelines across Meta product surfaces, including ranking, recommendation, and generative AI systems.
Own the end-to-end technical design of AI/ML systems, evaluate architectural trade-offs, and select modeling approaches, training strategies, and inference frameworks.
Instrument and profile ML training and serving pipelines to identify bottlenecks, reduce latency, and optimize compute efficiency at scale.
Establish and maintain model evaluation frameworks, including offline metrics, online experimentation, and monitoring, to ensure production model quality and reliability.
Collaborate with product managers, data scientists, and research scientists to translate product requirements into ML problem formulations and deliver measurable improvements to key metrics.
Build reusable AI tooling and infrastructure components, improve developer workflows, and promote best practices in model development and deployment.
Apply privacy-by-design principles and integrity safeguards throughout the ML development lifecycle, and partner with cross-functional teams on data governance and compliance requirements.
Mentor engineers on ML system design, modeling techniques, and engineering craft, and contribute to recruiting and technical community programs.
Use AI-augmented development workflows to expand work across data analysis, product thinking, and operational readiness.
Drive staged rollouts of new models using feature flagging and A/B testing frameworks, monitor for regressions, and lead incident retrospectives to prevent recurrence.